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Study on flexible job shop scheduling problem considering energy saving J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 Yanjun Xiao, Shanshan Yin, Guoqing Ren, Weiling Liu
The Flexible Job Shop Scheduling Problem (FJSP) is an extension of the classical Job Shop Scheduling Problem (JSP). The research objective of the traditional FJSP mainly considers the completion time, but ignores the energy consumption of the manufacturing system. In this paper, a mathematical model of the energy-efficient flexible job shop scheduling problem is constructed. The optimization objectives
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Implementation of a dynamic planning algorithm in accounting information technology administration J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 Yuan Gao
Accounting professionals are increasingly being encouraged to shift their focus from conventional accounting to accounting information as a result of new management strategies and ideas. Cybercrime and other attempts to exploit weaknesses in online systems have become more common in recent years. By introducing the concept of cloud computing and analyzing its logical structure, this research applies
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Handling syntactic difference in Chinese-Vietnamese neural machine translation J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 Zhiqiang Yu, Ting Wang, Shihu Liu, Xuewen Tan
As the typical distant language pair, Chinese and Vietnamese vary widely in syntactic structure, which significantly influences the performance of Chinese-Vietnamese machine translation. To address this problem, we present a simple approach with a pre-reordering model for closing syntactic gaps ofthe Chinese-Vietnamese language pair. Specifically, we first propose an algorithm for recognizing the modifier
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A Novel Constructing Continuous and Topology Approach to Fuzzy β-covering J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 Hongxuan He, Pei Wang, Jiakuan Lu
Fuzzy β-covering(Fβ-C) plays a key role in processing real-valued data sets and covering plays an important role in the topological spaces. Thus they have attracted much attention. But the relationship between Fβ-C and topology has not been studied. This inspires the research of Fβ-C from the perspective of topology. In this paper, we construct Fβ-C rough continuous and homeomorphism mappings by using
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DBSCAN-based energy users clustering for performance enhancement of deep learning model J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 Khursheed Aurangzeb
Background:Due to rapid progress in the fields of artificial intelligence, machine learning and deep learning, the power grids are transforming into Smart Grids (SG) which are versatile, reliable, intelligent and stable. The power consumption of the energy users is varying throughout the day as well as in different days of the week. Power consumption forecasting is of vital importance for the sustainable
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Intelligent decision support system for pulmonary tuberculosis detection using bipolar fuzzy utility matrix and bipolar Mamdani fuzzy inference system J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 Ezhilarasan Natarajan, Felix Augustin
Tuberculosis (TB) stands as the second leading global infectious cause of death, following closely behind the impact of COVID-19. The standard approach to diagnose TB involves skin tests, but these tests can yield inaccurate results due to limited access to healthcare and insufficient diagnostic resources. To enhance diagnostic accuracy, this study introduces a novel approach employing a Bipolar Fuzzy
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Ranking DMUs by using interval efficiencies in data envelopment analysis J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 Xing-Xian Zhang, Wenli Liu, Xu Wang, Wenjin Zuo, Ying-Ming Wang, Licheng Sun
Efficiency is a relative measure that allows assessment across different ranges. Evaluating the performance of decision-making units (DMUs) from an optimistic perspective yields the best relative efficiency (optimistic efficiency), which establishes an efficiency frontier. Conversely, evaluating from a pessimistic perspective produces the worst relative efficiency (pessimistic efficiency) and creates
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Object-oriented concept acquisition based on attribute topology J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 Kuo Pang, Yifan Lu, Lixian Xu, Wei Yan, Li Zou, Mingyu Lu
The research of object-oriented concept is one of the basic contents of formal concept analysis. To overcome the complexity of computing object-oriented concept, this paper proposes an Object-oriented Concept Acquisition model (OCA) based on attribute topology. The object-oriented attribute topology is first proposed to visualize the coupling relationship between attributes. Second, inspired by rough
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Diagnosis of skin lesion using shift-invariant network and an improved grey wolf optimizer J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 V. Sharmila, P. Ezhumalai
The global incidence of skin cancer has been rising, resulting in increased mortality and morbidity if left untreated. Accurate diagnosis of skin malignancies is crucial for early intervention through excision. While various innovative medical imaging techniques, such as dermoscopy, have improved the way we examine skin cancers, the progress in medical imaging for identifying skin lesions has not kept
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Computer multimedia aided design and hand-drawn effect analysis based on grid resource sharing cooperative algorithm J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-03-05 Xiaohong Gu
Hand-drawn is one of the few visual descriptors that can directly represent visual content, and has significant research in the area of computer vision. Aiming at the problem of sparse features in the realm of hand-drawn image retrieval, hand-drawn images, and the easy deformation of hand-drawn images, this paper proposes a feature extraction method of grid resource sharing collaborative algorithm
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Fair and stable matching decision-making with multiple hesitant fuzzy elements J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 Qi Yue, Zhibin Deng, Bin Hu, Yuan Tao
The two-sided matching (TSM) decision-making is an interdisciplinary research field encompassing management science, behavioral science, and computer science, which are widely applied in various industries and everyday life, generating significant economic and social value. However, in the decision-making process of real-world TSM, the complexity of the decision-making problem and environment lead
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An improved clustering method using particle swarm optimization algorithm and mitochondrial fusion model (PSO-MFM) J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 Mohammed M. Nasef, Passent M. El Kafrawy, Amal Hashim
Computational models are foundational concepts in computer science; many of these models such as P systems are based on natural biological processes. P systems represent a wide framework for a variety of concepts of data mining, as models of data clustering approaches. Data clustering is a technique for analyzing data based on its structure that is widely utilized for many applications. In this paper
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A total distance ranking approach to fuzzy AHP-based MCDM method for selecting sustainable manufacturing facility location J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 Thi Bich Ha Nghiem, Ta-Chung Chu
Selecting a sustainable facility location is a crucial strategy for manufacturing companies to achieve long-term success in today’s competitive environment. Various quantitative and qualitative criteria with different importance in a multiple level structure must be considered and aggregated to assist the company in decision-making. How to determine these criteria weights and select the sustainable
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Research on social ecological evaluation of the spatial form of old urban blocks based on dual probabilistic linguistic term sets J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 Wenjuan Li, Xiduo Yi
Under the rapid process of urbanization, many early renovated urban villages have also encountered many problems. Due to the rapid development of urban construction and the continuous changes in spatial functions, early renovated urban villages have already encountered problems such as unreasonablecommercial distribution, lack of parking spaces, reduced commercial vitality, and commercial activities
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Using path coloring of graphs for communication in social networks J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 Dhanyashree, K.N. Meera, Said Broumi
An L (p1, p2, p3, … , pm)- labeling of a graph G, has the vertices of G assigned with non-negative integers, such that the vertices at distance j should have at least pj as their label difference. If m = 3 and p1 = 3, p2 = 2, p3 = 1, it is called an L (3, 2, 1)-labeling which is widely studied in the literature. In this paper, we define an L (3, 2, 1)-path coloring of G as a labeling g : V (G) → Z+
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Pythagorean fuzzy Aczel Alsina Hamy mean aggregation operators and its applications to multi-attribute decision-making process J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 Abrar Hussain, Sajid Latif, Kifayat Ullah, Harish Garg, Ashraf Al-Quran
Multiple-attribute group decision-making (MAGDM) technique is often used to make decisions when several optimal options are under consideration. It can be difficult to select a reasonable optimal option for the decision maker under consideration of insufficient information. The theory of Hamy mean(HM) operators are used to express correlation among different input arguments and provide a smooth approximation
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An integrated framework for spherical fuzzy MAGDM and applications to english blended teaching quality evaluation J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 Bin Xie
In the information age, teachers are no longer the only source of information for students, and the problems of the traditional lecture mode are becoming more and more obvious. Especially in the process of teaching English in colleges and universities, students’ personalized and diversified needs for English learning are becoming more and more obvious, and if traditional theoretical lectures or theoretical
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Smart intrusion detection system with balanced data in IoMT infra J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 S. Umamaheswaran, J. Mannar Mannan, K.M. Karthick Raghunath, Santhi Muttipoll Dharmarajlu, M.D. Anuratha
The IoMT (Internet of Medical Things) has allowed for uninterrupted, critical patient observation, improved diagnosis precision, and efficient therapy. However, despite the usefulness of such medical things (devices), they also raise a lot of confidentiality and security issues since they provide potential entry points for hackers to exploit. Therefore, there is a pressing need for a technique for
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The reptile optimized deep learning model for land cover classification of the uppal earth region in telangana state using satellite image fusion J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 P. Aruna Sri, V. Santhi
This study addresses challenges in land use and cover identification using remote sensing (RS) imagery, focusing on the Uppal region. By leveraging deep learning models, particularly an optimized ResNext-50 architecture, we aim to enhance efficiency and accuracy in classifying land features. Our approach integrates Landsat-8 and hyper-spectral satellite data, utilizing preprocessing techniques like
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T2FM: A novel hashtable based type-2 fuzzy frequent itemsets mining J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-02-14 M. Jeya Sutha, F. Ramesh Dhanaseelan, M. Felix Nes Mabel, V.T. Vijumon
Association rule mining (ARM) is an important research issue in the field of data mining that aims to find relations among different items in binary databases. The conventional ARM algorithms consider the frequency of the items in binary databases, which is not sufficient for real time applications. In this paper, a novel hash table based Type-2 fuzzy mining algorithm (T2FM) with an efficient pruning
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A probability-exponential method of converting Z-numbers and its systematic applications in multi-attribute decision making J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-25 Hong Sun, Xianyong Zhang
Z-numbers contain fuzzy restrictions, credibility measures, and probability distributions to effectively represent uncertain information. Converting Z-numbers to fuzzy numbers facilitates extensive applications (such as multi-attribute decision-making (MADM)), thus becoming valuable for research purposes. Regarding Z-number conversions, the original method never considers the association probability
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An optimal secure defense mechanism for DDoS attack in IoT network using feature optimization and intrusion detection system J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-19 J.S. Prasath, V. Irine Shyja, P. Chandrakanth, Boddepalli Kiran Kumar, Adam Raja Basha
Now, the Cyber security is facing unprecedented difficulties as a result of the proliferation of smart devices in the Internet of Things (IoT) environment. The rapid growth in the number of Internet users over the past two decades has increased the need for cyber security. Users have provided new opportunities for attackers to do harm. Limited security budgets leave IoT devices vulnerable and easily
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Revolutionizing collaborative auditing: A dynamic blockchain-based cloud storage framework for data updates and assurance J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-18 Ansar Isak Sheikh, M. Sadish Sendil, P. Sridhar, M.I. Thariq Hussan, Shafiqul Abidin, Ravi Kumar, Reyazur Rashid Irshad, Elangovan Muniyandy, Solleti Phani Kumar
Effective data management has arisen as a major concern in today’s era of ubiquitous data generation from a plethora of intelligent gadgets. While data proliferation promises unparalleled benefits, it imposes significant storage and computing constraints, particularly on end-users with limited capabilities. To solve these difficulties, this article investigates the confluence of cloud storage, blockchain
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Research on multi-task perception network of traffic scene based on feature fusion 1 J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-18 Duo Sui, Peng Gao, Minhang Fang, Jing Lian, Linhui Li
Aiming at the problems of low precision and low real-time performance when deploying to embedded platforms in existing multi-task networks, this paper proposes a traffic scene multi-task perception network model (ETS_YOLOP) based on feature fusion. Firstly, an Efficient Attention Control Aggregation Network Module (EACAN) is constructed to improve the real-time perception of the model, and the Space
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A study on the stratification of long-tail customers in civil aviation based on a cluster ensemble J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-18 Yi Zong, Ying Li, Enze Pan, Simin Chen, Jingkuan Zhang, Binbin Gao
Stratifying long-tail customers and identifying high-quality customers with high growth potential are crucial for civil aviation companies to explore new profit growth points. This paper proposes a long-tail customer stratification model based on clustering ensemble to address the problems of insufficient attention to long-tail customers in previous studies and the low accuracy and lack of accuracy
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A novel DAG-blockchain structure for trusted routing in secure MANET-IoT environment J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-17 N. Ilakkiya, A. Rajaram
Different physical objects can be employed in the modern technological environment to facilitate human activity. In order to connect physical objects with the universe of digital using a variety of networks and communication technologies, an IoT, the cutting edges technological and effective solution, is deployed. Mobile ad hoc networks (MANET) interact with the IoTin smart settings, enhancing its
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A novel grey fractional model based on model averaging for forecasting time series J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-17 Zhiyuan Ouyang, Yanlin Wang, Tao Zhang, Wen-Ze Wu
The introduction of fractional order accumulation has played a crucial role in the development of grey forecasting methods. However, accurately identifying a single fractional order accumulation for modeling diverse sequences is challenging due to the dependence of different fractional order accumulations on data structure over time. To address this issue, we propose a novel fractional grey model abbreviated
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Artificial intelligence-driven photovoltaic building materials industry: Greenization and digitization innovation conversion of photovoltaic technology based on a novel interval fuzzy field theory decision-making model J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-17 Nan Zhang, Jiayi Yin, Ning Zhang, Tongtong Sun, Shi Yin, Lijun Wan
Digital technologies, such as big data, the Internet, and artificial intelligence, are rapidly advancing. Photovoltaic building materials enterprises (PBMEs) have been leveraging digital transformation to enhance their technological innovation capabilities and gain a competitive edge. In the globalcontext of transitioning towards a low-carbon economy, the deep integration of digital technology offers
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Multi-objective shuffled frog leaping algorithm for deployment of sensors in target based wireless sensor networks J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 N. Poongavanam, N. Nithiyanandam, T. Suma, Venkata Nagaraju Thatha, Riaz Shaik
In this research, –coverage –connected problem is viewed as multi-objective problem and shuffling frog leaps algorithm is proposed to address multi-objective optimization issues. The shuffled frog leaping set of rules is a metaheuristic algorithm that mimics the behavior of frogs. Shuffled frog leaping algorithms are widely used to seek global optimal solutions by executing the guided heuristic on
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Integrated triangular fuzzy KE-GRA-TOPSIS method for dynamic ranking of products of customers’ fuzzy Kansei preferences J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 Dashuai Liu, Jie Zhang, Chenlu Wang, Weilin Ci, Baoxia Wu, Huafeng Quan
As society evolves, companies produce more homogeneous products, shifting customers’ needs from functionality to emotions. Therefore, how quickly customers select products that meet their Kansei preferences has become a key concern. However, customer Kansei preferences vary from person to person and are ambiguous and uncertain, posing a challenge. To address this problem, this paper proposes a TF-KE-GRA-TOPSIS
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An optimized fuzzy based FP-growth algorithm for mining temporal data J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 B. Praveen Kumar, T. Padmavathy, S.U. Muthunagai, D. Paulraj
Data mining is one of the emerging technologies used in many applications such as Market analysis and Machine learning. Temporal data mining is used to get a clear knowledge about current trend and to predict the upcoming future. The rudimentary challenge in introducing a data mining procedure is,processing time and memory consumption are highly increasing while trying to improve the accuracy, precision
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Multi-criteria group decision-making based on dombi aggregation operators under p, q-quasirung orthopair fuzzy sets J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 Muhammad Rahim, ElSayed M. Tag Eldin, Salma Khan, Nivin A. Ghamry, Agaeb Mahal Alanzi, Hamiden Abd El-Wahed Khalifa
In this study, we introduce The p, q-quasirung orthopair fuzzy Dombi operators, including p, q-quasirung orthopair fuzzy Dombi weighted averaging (p, q-QOFDWA), p, q-quasirung orthopair fuzzy Dombi ordered weighted averaging (p, q-QOFDOWA), p, q-quasirung orthopair fuzzy Dombi weighted geometric (p, q-QOFDWG), and p, q-quasirung orthopair fuzzy Dombi ordered weighted geometric (p, q-QOFDOWG) operators
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Enhanced EDAS technique for colleges business English teaching quality evaluation based on Euclid distance and cosine similarity measure J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 Yuan Yuan
With the development of national economy and the increase of foreign trade, Business English has become one of the most popular majors in universities. In order to cultivate business English talents for the national society and adapt to the requirements of the times, the innovation of English teaching concepts and the reform of teaching techniques are the only way for business English majors teaching
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Eigenproblems in addition-min algebra 1 J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 Meng Li, Xue-ping Wang
In order to guarantee the downloading quality requirements of users and improve the stability of data transmission in a BitTorrent-like peer-to-peer file sharing system, this article deals with eigenproblems of addition-min algebras. First, it provides a sufficient and necessary condition for a vector being an eigenvector of a given matrix, and then presents an algorithm for finding all the eigenvalues
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Predicting diabetic macular edema in retina fundus images based on optimized deep residual network techniques on medical internet of things J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 Vo Thi Hong Tuyet, Nguyen Thanh Binh, Dang Thanh Tin
With the medical internet of things, many automated diagnostic models related to eye diseases are easier. The doctors could quickly contrast and compare retina fundus images. The retina image contains a lot of information in the image. The task of detecting diabetic macular edema from retinal images in the healthcare system is difficult because the details in these images are very small. This paper
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Intuitionistic fuzzy geometric aggregation operators based on Yager’s triangular norms and its application in multi-criteria decision making J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 Weize Wang, Yurui Feng
Intuitionistic fuzzy (IF) information aggregation in multi-criteria decision making (MCDM) is a substantial stream that has attracted significant research attention. There are various IF aggregation operators have been suggested for extracting more informative data from imprecise and redundant rawinformation. However, some of the aggregation techniques that are currently being applied in IF environments
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Spin orbit magnetic random access memory based binary CNN in-memory accelerator (BIMA) with sense amplifier J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 K. Kalaichelvi, M. Sundaram, P. Sanmugavalli
The research tends to suggest a spin-orbit torque magnetic random access memory (SOT-MRAM)-based Binary CNN In-Memory Accelerator (BIMA) to minimize power utilization and suggests an In-Memory Computing (IMC) for AdderNet-based BIMA to further enhance performance by fully utilizing the benefits ofIMC as well as a low current consumption configuration employing SOT-MRAM. And recommended an IMC-friendly
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Determination of multi-UAVs formation shape: Using a requirement satisfaction and spherical fuzzy ANP based TOPSIS approach J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 An Zhang, Minghao Li, Wenhao Bi
Multiple unmanned aerial vehicles (multi-UAVs) formation shape refers to the geometric shape when multi-UAVs fly in formation and describes their relative positions. It plays a necessary role in multi-UAVs collaboration to improve performance, avoid collision, and provide reference for control. This study aims to determine the most appropriate multi-UAVs formation shape in a specific mission to meet
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Enhanced group decision-making framework for financial performance evaluation of high-tech enterprises under interval neutrosophic environment J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-11 Heng Li
The financial performance of enterprises has always been the key to their survival and development, especially for high-tech enterprises. Evaluating the financial performance of high-tech enterprises is beneficial for the management department to accurately understand the financial situation of theenterprise, timely identify financial problems, and study solutions based on this; On the other hand,
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A 2TLNS-based exponential TODIM-EDAS approach for evaluating sustainable development of cross-border e-commerce platforms under uncertainty J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-11 Fang Xu
In the context of globalization, cross-border e-commerce platforms have become the main way for enterprises to achieve international trade transformation and overseas investment. From this, it can be seen that cross-border e-commerce platforms are of great importance to the development of enterprises, and the development of cross-border e-commerce platforms is also a necessary choice for the development
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A machine learning-based data-driven approach to Alzheimer’s disease diagnosis using statistical and harmony search methods J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-11 Pouya Bolourchi, Mohammadreza Gholami
Alzheimer’s disease (AD) is the most prevalent brain disorder which affects millions of people worldwide. Early detection is crucial for possible treatment. In this regard, machine learning (ML) approaches are widely utilized for AD detection. In this paper, we propose an ML-based method that drastically reduces the dimensionality of features while maintaining the relevant features and boosting the
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A fuzzy rough granular ensemble learning based on the feature selection with chi-square 1 J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-11 Xianyu Hou, Yumin Chen, Keshou Wu, Ying Zhou, Junwen Lu, Xuan Weng
Neighborhood granulation is a classical granulation method. Although it is adequate for clustering and classification tasks, its granules are more complex, and the data representation is binary. This paper proposes a new granulation method based on the neighborhood granulation. Firstly, a detaileddefinition of the granular form is given with fuzzy rough set theory. Then, a modified fuzzy rough discriminant
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Research on the urban green transportation development level evaluation based on the triangular pythagorean fuzzy multiple attribute decision making J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2024-01-10 Huan Yu
With the acceleration of urbanization and the significant improvement of people’s living standards, the motorization of urban transportation in China has developed rapidly, and the number of urban motor vehicles has sharply increased. This has also caused a series of problems such as increasingly severe urban road traffic congestion, increased traffic energy consumption, and atmospheric environmental
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Privacy-preserving fuzzy commitment schemes for secure IoT device authentication J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-12-16 M. Kandan, A. Durai Murugan, Gandikota Ramu, Gandikota Ramu, R.K. Gnanamurthy, Dibyahash Bordoloi, Swati Rawat, Murugesan, Pulicherla Siva Prasad
Privacy-Preserving Fuzzy Commitment Schemes (PPFCS) have emerged as a promising solution for secure Internet of Things (IoT) device authentication, addressing the critical need for privacy and security in the rapidly growing IoT ecosystem. This paper presents a novel PPFCS-based authentication mechanism that protects sensitive user data and ensures secure communication between IoT devices. The proposed
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Enhanced edge detection model for low resolution images J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-12-15 D.M. Deepak Raj, A. Arulmurugan, G. Shankar, A. Arthi, Vijaya Babu Panthagani, C.H. Sandeep
The technique of determining the borders between several objects or regions in an image is known as edge detection. The edges of an object in an image serve as the object’s limits and can reveal crucial details about the object’s size, shape, and position. The pre-processing stage of edge detectionis crucial because it can increase the precision and effectiveness of edge detection algorithms. As low-density
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Fuzzy-enhanced adaptive multi-layered cloud security framework leveraging artificial intelligence, quantum-resistant cryptography, and fuzzy systems for robust protection J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-12-15 F. Niyasudeen, M. Mohan
With the growing reliance on cloud computing, ensuring robust security and data protection has become a pressing concern. Traditional cryptographic methods face potential vulnerabilities in the post-quantum era, necessitating the development of advanced security frameworks. This paper presents a fuzzy-enhanced adaptive multi-layered cloud security framework that leverages artificial intelligence, quantum-resistant
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Automatic detection method of small target in tennis game video based on deep learning J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-12-02 Danna Gao, Yin Zhang, Hongjun Qiu
Due to the large number of frames and low video resolution, tennis match videos cannot accurately identify and extract effective data, which reduces the level of fine analysis of tennis matches. In order to solve the problem of poor detection effect of small targets in tennis video, an automatic detection method of small targets in tennis video based on deep learning is proposed. Non-maximum suppression
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Vocal music teaching method using fuzzy logic approach for musical performance evaluation J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-12-02 Xiaoquan He, Fang Dong
Vocal music teaching through E-learning platforms and in-person classrooms requires intense attention and practice. The vocals and strings with/without instrument support are required for improving the voice, pitch presentation, and learning improvement. With digitalization, the assessments are performed using a computer and process-aided technologies for musical performance evaluation. This article
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Metaverse-oriented visual art quality enhancement strategies: a field architecture design and fuzzy assessment theory perspective J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-12-02 Zhang Xinyi
Visual art was originally measured by viewing and appreciating graphic works, and there was no previous research into ways to improve the quality of visual art. With the rapid development of visual arts and technology, the question of how to improve quality has become an urgent one. As the most cutting-edge and hottest concept in the international arena today, the development and application of metaverse
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Risk assessment method for large-section tunnel using neutrosophic numbers similarity measure based on arcsine function J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-12-02 Shaohua Liu, Caichu Xia, Jun Ye
In large-section tunnel engineering, there is uncertain and inconsistent information in risk factors, due to complex geological, irregular hydrological conditions, limited survey technology, and inexperience of construction technicians. However, it is difficult for existing risk assessment methodsto consider and express this uncertain information comprehensively, which will affect the accuracy of tunnel
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Lung cancer detection using RF-K-means and classification with optimized ANN algorithm J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-12-06 O. Kalaipriya, S. Dhandapani
Lung cancer is one of the leading causes of mortality from cancer. Lung cancer is a kind of malignant lung tumor characterized by uncontrolled cell proliferation in lung tissues. Even though CT scans are the most often used imaging technology in medicine, clinicians find it challenging to interpretand diagnose cancer from CT scan pictures. As a result, computer-aided diagnostics can assist clinicians
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Deep learning and optimization-based task scheduling algorithms for fog-cloud computing environment J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-12-01 Ayoobkhan Mohamed Uvaze Ahamed, D.J. Joel Devadass Daniel, D. Seenivasan, C. Rukumani Khandhan, S. Radhakrishnan, K.V. Daya Sagar, Vivek Bhardwaj, Neerav Nishant
Time-sensitive programs that are linked to smart services, such as smart healthcare as well as smart cities, are supported in large part by the fog computing domain. Due to the increased speed limitation of the cloud, Cloud Computing (CC) is a competent platform for fog in data processing, but it is unable to meet the demands of time-sensitive programs. The procedure of resource provisioning, as well
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Detection of mapping function location observation with displacement in organising model by using deep learning J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-11-30 M. Pradeep, U. Sivaji, B. Nithya, G. Kadiravan, D. Preethi, Ranjith Kumar Painam
The mapping function must identify the reference model and detect coordinate arrangement by observing a repository with deep learning. Progression model with coordinate arrangement composition should have various positional displacements from one location to another. A prerogative classification model is an evolution of factor accomplishment in a repository method. Coordinate arrangement with calculation
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Prediction of stock market using grey wolf optimization with hybrid convolutional neural network and bi-directional long-short term memory model J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-11-24 Yedhu Harikumar, M. Muthumeenakshi
The Indian stock market is a dynamic, complicated system that is impacted by many different variables, making it difficult to anticipate its future. The utilization of deep learning and optimization techniques to forecast stock market movements has gained popularity in recent years. To foresee theIndian stock market, an innovative approach is presented in this study that combines the Grey Wolf Optimization
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Enhancing the feature selection by employing improved optimization with Simulated Annealing Algorithm for dimensionality reduction in intrusion detection dataset J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-11-10 A. Arulmurugan, G. Jose Moses, Ongole Gandhi, M. Sheshikala, A. Arthie
In the current scenario, feature selection (FS) remains one of the very important functions in machine learning. Decreasing the feature set (FSt) assists in enhancing the classifier’s accuracy. Because of the existence of a huge quantity of data within the dataset (DS), it remains a colossal procedure for choosing the requisite features out of the DS. Hence, for resolving this issue, a new Chaos Q
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Artificial algae optimizer with hybrid deep learning based yoga posture recognition model J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-11-10 Nagalakshmi Vallabhaneni, Panneer Prabhavathy
Numerous people are interested in learning yoga due to the increased tension levels in the modern lifestyle, and there are a variety of techniques or resources available. Yoga is practiced in yoga centers, by personal instructors, and through books, the Internet, recorded videos, etc. As the aforementioned resources may not always be available, a large number of people will opt for self-study in fast-paced
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A combined neural network mechanism for categorizing the normal and cancer cells J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-11-04 M.S. Antony Vigil, Amit Agarwal, K.B.V. Brahma Rao, G. Meena Devi, Mohd Umar Farooq, P. Ganeshan, Nouf M. Alyami, Rafa Almeer, S.S. Raghavan
The dangerous form of acute lymphocytic leukemia damages the bone marrow tissue and white blood cells. Unformed white blood cells multiply and exchange healthy cells in the bone marrow. Everything spreads fast and, if not noticed, can be dangerous in some months. As a result, computer assisted diagnosis of acute lymphocytic leukemia has the possible to protect several lives, but it needs a high-precision
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A hybrid multi-criteria decision-making framework of EWM-BWM-TODIM based on Linguistic Pythagorean fuzzy environment J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-11-04 Jianping Fan, Min Wang, Meiqin Wu
Linguistic Pythagorean fuzzy set (LPFS) combines Pythagorean fuzzy sets and linguistic term sets, which can effectively deal with fuzzy information in multi-criteria decision-making (MCDM). The entropy weight method (EWM) can reflect the objectivity of decision information, while the best-worst method (BWM) can reflect the subjectivity of decision-makers. The interactive multi-criteria decision-making
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Region-Attention Prompt Learning for CLIP J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-11-04 Yiming Pan, Hua Cheng, Yiquan Fang, Yufei Liu
Pre-trained Visual Language Models (VLMs) like CLIP have shown great potential in the multimodal domain. Among this, using different modal contexts and interaction features to construct prompt can stimulate the model’s prior knowledge circuit more accurately, thus generating better outputs. However, in CLIP, the formal mismatch of textual descriptions between the pre-training and inference phases results
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A probabilistic neural network with adaptive capability to optimize fault trees for the intelligent fault diagnosis of rapier loom throughout its operating cycle 1 J. Intell. Fuzzy Syst. (IF 2.0) Pub Date : 2023-11-04 Yanjun Xiao, Yue Zhao, Furong Han, Kai Peng, Feng Wan
The mechanical structures of the rapier loom are strongly coupled, resulting in faults that are characterized by strong coupling, hierarchy, phase dynamics, and a transient nature. However, current fault diagnosis methods using a single approach are not satisfactory. Additionally, fault diagnosis of the entire operation cycle of the rapier loom equipment is lacking. This paper proposes a fault tree