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An improved grid search algorithm to optimize SVR for prediction Soft Comput. (IF 3.05) Pub Date : 2021-01-20 Yuting Sun, Shifei Ding, Zichen Zhang, Weikuan Jia
Parameter optimization is an important step for support vector regression (SVR), since its prediction performance greatly depends on values of the related parameters. To solve the shortcomings of traditional grid search algorithms such as too many invalid search ranges and sensitivity to search step, an improved grid search algorithm is proposed to optimize SVR for prediction. The improved grid search
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Fast neighbor user searching for neighborhood-based collaborative filtering with hybrid user similarity measures Soft Comput. (IF 3.05) Pub Date : 2021-01-18 Zepeng Li, Li Zhang
In neighborhood-based collaborative filtering (NBCF) algorithms, user similarity measures have a great effect on the performance of collaborative filtering (CF). Researchers have proposed some schemes of hybrid user similarity and applied them to recommendation systems (RSs). However, hybrid user similarity measures suffer from a time-consuming issue when searching neighbor users using these schemes
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Analysis of autocorrelation function of stochastic processes by F-transform of higher degree Soft Comput. (IF 3.05) Pub Date : 2021-01-18 Michal Holčapek, Linh Nguyen
The autocorrelation function of a stochastic process is one of the essential mathematical tools in the description of variability that is successfully applied in many scientific fields such as signal processing or financial time series analysis and forecasting. The aim of the paper is to provide an analysis of fuzzy transform of higher degree applied to stochastic processes with a focus on its autocorrelation
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The influence of uncertainties on optimization of vaccinations on a network of animal movements Soft Comput. (IF 3.05) Pub Date : 2021-01-18 Krzysztof Michalak, Mario Giacobini
In this article, multiobjective optimization of vaccinations is studied using graph-based modelling and simulations of the spreading of the disease. Real-life dataset of animal movements between farms and pastures in the Piedmont region of Italy is used, from which a dynamic network of contacts is reconstructed. Evolutionary multiobjective optimization of vaccinations is compared with vaccination strategies
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Approximate solutions of fuzzy optimal control problems using sigmoid-weighted neural networks Soft Comput. (IF 3.05) Pub Date : 2021-01-18 Saeed Panahian Fard, Rahim Pourabbas, Jafar Pouramini
Optimal control problem is one of the most challenging subjects in control theory. It has numerous applications in science and engineering. In this study, we are motivated to obtain the solution of fuzzy optimal control problems via universal approximation capability of a single-layer feedforward artificial neural network. First, we transform the fuzzy optimal control problems into systems of first-order
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An improved thermodynamic simulated annealing-based approach for resource-skewness-aware and power-efficient virtual machine consolidation in cloud datacenters Soft Comput. (IF 3.05) Pub Date : 2021-01-18 Pedram Saeedi, Mirsaeid Hosseini Shirvani
Cloud computing attracted great attention in both industry and research communities for the sake of its ubiquitous, elasticity and economic services. The first class concern of cloud providers is power management for both reducing their total cost of ownership and green computing objectives. To reach the goal, a system framework is presented which has different modules. The main concentration of the
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Confidence-aware collaborative detection mechanism for false data attacks in smart grids Soft Comput. (IF 3.05) Pub Date : 2021-01-16 Zhuoqun Xia, Gaohang Long, Bo Yin
Nowadays, the false data injection attack (FDIA), which can bring inestimable losses to smart grids, has become one of the most threatening cyber attacks in cyber physical systems. Previous studies for false data detection focused on state estimation, which require a huge computational overhead at the control center. In this paper, we propose a confidence-aware collaborative detection mechanism for
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An improved case-based reasoning method and its application to predict machining performance Soft Comput. (IF 3.05) Pub Date : 2021-01-16 Longhua Xu, Chuanzhen Huang, Jiahui Niu, Chengwu Li, Jun Wang, Hanlian Liu, Xiaodan Wang
In the machining process, the machining performance which mainly refers to machined surface quality and cutting forces is hard to predict under different tool wear status. In this work, an improved case-based reasoning (ICBR) method is proposed to predict both the cutting force and machined surface roughness. With the emergence of new problem, ICBR method obtains solutions to new problem through case
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Generalized multigranulation fuzzy rough sets based on upward additive consistency Soft Comput. (IF 3.05) Pub Date : 2021-01-16 Noor Rehman, Abbas Ali
In this paper, we point out that the transfer function for computing the fuzzy preference degree of Pan et al. (Fuzzy Sets Syst 312:87–108, 2017) for the construction of upward/downward fuzzy relations is not additive consistent. Appropriate counterexample is given. Further their modified versions are presented. Meanwhile, we construct upward consistency matrices of experts which satisfy the upward
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Theoretical justifications for the empirically successful VIKOR approach to multi-criteria decision making Soft Comput. (IF 3.05) Pub Date : 2021-01-16 Muhammad Jabir Khan, Poom Kumam, Wiyada Kumam
In many practical applications, we have several different criteria for making a decision. In such situations, we need to take all these criteria into account. One of the most widely used approaches for solving such multi-criteria decision making problems was proposed in 1979 by S. Opricovic; it is known as VIKOR. This approach has been widely and successfully used—to the extent that the corresponding
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Selection of optimal software reliability growth model using a diversity index Soft Comput. (IF 3.05) Pub Date : 2021-01-16 Tahere Yaghoobi
Software reliability growth models (SRGMs) have been arisen to estimate various criteria such as the number of errors remaining in the software, the software failure rate, and determining the reliability of the software. In general, SRGMs are dataset dependent and hence the selection of an optimal model for use in a particular application is considered an important issue in software reliability engineering
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Generalisation and robustness investigation for facial and speech emotion recognition using bio-inspired spiking neural networks Soft Comput. (IF 3.05) Pub Date : 2021-01-16 Esma Mansouri-Benssassi, Juan Ye
Emotion recognition through facial expression and non-verbal speech represents an important area in affective computing. They have been extensively studied from classical feature extraction techniques to more recent deep learning approaches. However, most of these approaches face two major challenges: (1) robustness—in the face of degradation such as noise, can a model still make correct predictions
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UAVData: A dataset for unmanned aerial vehicle detection Soft Comput. (IF 3.05) Pub Date : 2021-01-16 Yuni Zeng, Qianwen Duan, Xiangru Chen, Dezhong Peng, Yao Mao, Ke Yang
The unmanned aerial vehicles (UAVs) significantly contribute to the convenience and intelligence of life. However, the large use of UAVs also leads to high security risk. Only detecting the small and flying UAVs can prevent the safety accidents. UAV detection task could be regarded as a branch of object detection in flied of image processing. The advanced object detection models are mainly data driven
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Minor-embedding heuristics for large-scale annealing processors with sparse hardware graphs of up to 102,400 nodes Soft Comput. (IF 3.05) Pub Date : 2021-01-16 Yuya Sugie, Yuki Yoshida, Normann Mertig, Takashi Takemoto, Hiroshi Teramoto, Atsuyoshi Nakamura, Ichigaku Takigawa, Shin-ichi Minato, Masanao Yamaoka, Tamiki Komatsuzaki
Minor-embedding heuristics have become an indispensable tool for compiling problems in quadratically unconstrained binary optimization (QUBO) into the hardware graphs of quantum and CMOS annealing processors. While recent embedding heuristics have been developed for annealers of moderate size (about 2000 nodes), the size of the latest CMOS annealing processor (with 102,400 nodes) poses entirely new
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Correction to: Deep reinforcement learning for multi-objective placement of virtual machines in cloud datacenters Soft Comput. (IF 3.05) Pub Date : 2021-01-15 Luca Caviglione, Mauro Gaggero, Massimo Paolucci, Roberto Ronco
Page 2: Column 2, lines 2-4, previously read: “Specifically, we consider a decision maker that, after a proper training, is able to select the most suitable heuristic for compute the placement for each VM requested by end users”.
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SCTM: a self-controlled touring and movement for industrial autonomous vehicle navigation Soft Comput. (IF 3.05) Pub Date : 2021-01-15 Aldosary Saad, Ahmed M. Shehata
In recent days, the smart industry concept is becoming more prominent in industrial autonomous vehicle navigation systems. The need for service reliability and industrial management has led to various developing ideas in the industrial environment. Autonomous vehicles are commonly used for logistics and demand-aware migration of goods within the industry. In this article, the self-controlled touring
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Influencing factors analysis and development trend prediction of population aging in Wuhan based on TTCCA and MLRA-ARIMA Soft Comput. (IF 3.05) Pub Date : 2021-01-15 Congjun Rao, Yun Gao
With the rapid development of the economy, the problem of population aging has become increasingly prominent. To analyse the key factors affecting population aging effectively and predict the development trend of population aging timely are of great significance for formulating relevant policies scientifically and reasonably, which can mitigate the effects of population aging on society. This paper
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Clustering based on whale optimization algorithm for IoT over wireless nodes Soft Comput. (IF 3.05) Pub Date : 2021-01-15 Seyed Mostafa Bozorgi, Mahdi Rohani Hajiabadi, Ali Asghar Rahmani Hosseinabadi, Arun Kumar Sangaiah
IoT or Internet of Things can improve the possibility of interaction between various smart components in real time. In the infrastructure of IoT, wireless sensors can be used in order to reduce communication costs. Despite having positive effects, using wireless nodes add some challenges to the system. Limited resources, such as energy, CPU power and memory, are the main concerns in this technology
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LSD-based adaptive lane detection and tracking for ADAS in structured road environment Soft Comput. (IF 3.05) Pub Date : 2021-01-15 Jun Tian, Shiwang Liu, Xunyu Zhong, Jianping Zeng
Lane recognition is important for safe driving in structured road environment; it is becoming an indispensable part of the advanced driver-assistance system (ADAS) for active security control. This paper proposes a novel lane detection and tracking approach for ADAS by using the line segment detector (LSD), adaptive angle filter and dual Kalman filter. In the lane detection process, the region of interest
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An improved adaptive hybrid firefly differential evolution algorithm for passive target localization Soft Comput. (IF 3.05) Pub Date : 2021-01-13 Maja B. Rosić, Mirjana I. Simić, Predrag V. Pejović
This paper considers a passive target localization problem based on the noisy time of arrival measurements obtained from multiple receivers and a single transmitter. The maximum likelihood (ML) estimator for this localization problem is formulated as a highly nonlinear and non-convex optimization problem, where conventional optimization methods are not suitable for solving such a problem. Consequently
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A hybrid method for biometric authentication-oriented face detection using autoregressive model with Bayes Backpropagation Neural Network Soft Comput. (IF 3.05) Pub Date : 2021-01-13 M. Vasanthi, K. Seetharaman
This paper proposes a novel method, which is coined as ARBBPNN, for biometric-oriented face detection, based on autoregressive model with Bayes backpropagation neural network (BBPNN). Firstly, the given input colour key face image is modelled to HSV and YCbCr models. A hybrid model, called HS–YCbCr, is formulated based on the HSV and YCbCr models. The submodel, H, is divided into various sliding windows
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Optimization using the firefly algorithm of ensemble neural networks with type-2 fuzzy integration for COVID-19 time series prediction Soft Comput. (IF 3.05) Pub Date : 2021-01-13 Patricia Melin, Daniela Sánchez, Julio Cesar Monica, Oscar Castillo
In this paper, the latest global COVID-19 pandemic prediction is addressed. Each country worldwide has faced this pandemic differently, reflected in its statistical number of confirmed and death cases. Predicting the number of confirmed and death cases could allow us to know the future number of cases and provide each country with the necessary information to make decisions based on the predictions
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Choquet integral Jensen’s inequalities for set-valued and fuzzy set-valued functions Soft Comput. (IF 3.05) Pub Date : 2021-01-13 Deli Zhang, Caimei Guo, Degang Chen, Guijun Wang
This article attempts to establish Choquet integral Jensen’s inequality for set-valued and fuzzy set-valued functions. As a basis, the existing real-valued and set-valued Choquet integrals for set-valued functions are generalized, such that the range of the integrand is extended from \(P_{0}(R^{+})\) to \(P_{0}(R)\), the upper and lower Choquet integrals are defined, and the fuzzy set-valued Choquet
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An extension method for fully fuzzy Sylvester matrix equation Soft Comput. (IF 3.05) Pub Date : 2021-01-13 Liangshao Hou, Jieyong Zhou, Qixiang He
An extension method is proposed to solve a class of fully fuzzy Sylvester matrix equation (FFSME) under some mild assumptions. This method consists of two steps. Firstly, the fully fuzzy system is transferred into a series of interval Sylvester matrix equations through \(\alpha \)-cut. Secondly, these interval systems are extended into crisp systems which is easy to be solved. The solutions of FFSME
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Experimental investigation and comparative machine-learning prediction of compressive strength of recycled aggregate concrete Soft Comput. (IF 3.05) Pub Date : 2021-01-13 S. Reza Salimbahrami, Reza Shakeri
In this study, the idea of recycling the concrete wastes and reuse of them for reproduction of green concrete has been presented. Thus, we have tried to study mechanical parameters using recycled aggregate concrete. For this purpose, three mix designs including natural, recycled and recycled fiber concrete were tested. Moreover, at the end of the paper, estimation of compressive strength using ANN
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A general approach to fuzzy regression models based on different loss functions Soft Comput. (IF 3.05) Pub Date : 2021-01-12 Amir Hamzeh Khammar, Mohsen Arefi, Mohammad Ghasem Akbari
In this paper, a new general approach is presented to fit a fuzzy regression model when the response variable and the parameters of model are as fuzzy numbers. In this approach, for estimating the parameters of fuzzy regression model, a new definition of objective function is introduced based on the different loss functions and under the averages of differences between the \(\alpha \)-cuts of errors
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MRI brain tumor segmentation and prediction using modified region growing and adaptive SVM Soft Comput. (IF 3.05) Pub Date : 2021-01-11 A. Srinivasa Reddy, P. Chenna Reddy
Magnetic resonance imaging (MRI) is one of the tumor diagnostic tools in any part of the body. Nowadays, the brain tumor is becoming a major cause of the death of many individuals. The seriousness of a brain tumor is very big among all the variety of cancers, so to save a life immediate detection and proper treatment to be done. Detection of these cells is a difficult problem, because of the formation
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Investigation and prioritization of risk factors in the collision of two passenger trains based on fuzzy COPRAS and fuzzy DEMATEL methods Soft Comput. (IF 3.05) Pub Date : 2021-01-11 Araz Hasheminezhad, Farhad Hadadi, Hamid Shirmohammadi
Identifying the critical risk factors in train accidents play a vital role in the prevention of their recurrence in the future. However, this is a complex procedure due to the fact that it includes decision making and depends on a large number of relevant factors. In order to resolve this problem, first, this study made an effort to identify the risk factors in the collision of two passenger trains
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Achieving query performance in the cloud via a cost-effective data replication strategy Soft Comput. (IF 3.05) Pub Date : 2021-01-11 Uras Tos, Riad Mokadem, Abdelkader Hameurlain, Tolga Ayav
Meeting performance expectations of tenants without sacrificing economic benefit is a tough challenge for cloud providers. We propose a data replication strategy to simultaneously satisfy both the performance and provider profit. Response time of database queries is estimated with the consideration of parallel execution. If the estimated response time is not acceptable, bottlenecks are identified in
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Bonferroni mean operators of generalized trapezoidal hesitant fuzzy numbers and their application to decision-making problems Soft Comput. (IF 3.05) Pub Date : 2021-01-11 Irfan Deli
Generalized trapezoidal hesitant fuzzy numbers are useful when ever there is indecision among several possible values for the preferences over objects in the process of decision making. In this sense, the aim of this work is to investigate the multiple attribute decision-making problems with generalized trapezoidal hesitant fuzzy numbers (GTHF-numbers). Therefore, we develop two aggregation techniques
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Extended PROMETHEE method with Pythagorean fuzzy sets for medical diagnosis problems Soft Comput. (IF 3.05) Pub Date : 2021-01-10 Mahatab Uddin Molla, Bibhas C. Giri, Pranab Biswas
Pythagorean fuzzy sets, a generalization of intuitionistic fuzzy sets, can effectively handle uncertain, incomplete and inconsistent information involved in real-life multi-criteria decision making (MCDM) problems. Preference ranking organization method for enrichment of evaluation (PROMETHEE) is one of the popular methods for solving MCDM problem. In this paper, we extend the PROMETHEE method with
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Correction to: A new emergency response of spherical intelligent fuzzy decision process to diagnose of COVID19 Soft Comput. (IF 3.05) Pub Date : 2021-01-09 Shahzaib Ashraf, Saleem Abdullah, Alaa O. Almagrabi
This work was supported by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under grant No. (D-579-611-1441). The authors, therefore, gratefully acknowledge DSR technical and financial support.
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Solving engineering optimization problems using an improved real-coded genetic algorithm (IRGA) with directional mutation and crossover Soft Comput. (IF 3.05) Pub Date : 2021-01-09 Amit Kumar Das, Dilip Kumar Pratihar
Genetic algorithm (GA) is used to solve a variety of optimization problems. Mutation operator also is responsible in GA for maintaining a desired level of diversity in the population. Here, a directional mutation operator is proposed for real-coded genetic algorithm (RGA) along with a directional crossover (DX) operator to improve its performance. These evolutionary operators use directional information
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Face feature extraction for emotion recognition using statistical parameters from subband selective multilevel stationary biorthogonal wavelet transform Soft Comput. (IF 3.05) Pub Date : 2021-01-09 R. Jeen Retna Kumar, M. Sundaram, N. Arumugam, V. Kavitha
Facial expression recognition is an extensive aspect in the field of pattern recognition and affective computing. Recognizing emotions by facial expression is an imperative action to design control-oriented and human computer interactive applications. Facial expression recognition is probable by the motion of facial muscles resulting in the appearance variation of face features. Accurate feature extraction
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Recommending pull request reviewers based on code changes Soft Comput. (IF 3.05) Pub Date : 2021-01-09 Xin Ye, Yongjie Zheng, Wajdi Aljedaani, Mohamed Wiem Mkaouer
Pull-based development supports collaborative distributed development. It enables developers to collaborate on projects hosted on GitHub. If a developer wants to collaborate on a project, he/she will fork the repository, make modifications on the forked repository and send a pull request to the development team to ask for a merge of the code changes to the official repository. When the development
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A novel technique for the detection of myocardial dysfunction using ECG signals based on hybrid signal processing and neural networks Soft Comput. (IF 3.05) Pub Date : 2021-01-08 Wei Zeng, Jian Yuan, Chengzhi Yuan, Qinghui Wang, Fenglin Liu, Ying Wang
Heart disease prevention is one of the most important tasks for healthcare problems since more than 50 million people around the world are at the risk of cardiovascular disease. Traditionally, electrocardiography (ECG) signals play an important role in the diagnosis of cardiac disorder and arrhythmia detection since they reflect all the electrical activities of the heart. In the present study, we propose
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On the circulant intuitionistic fuzzy matrices Soft Comput. (IF 3.05) Pub Date : 2021-01-08 E. G. Emam
In this paper, we define fuzzy matrices (FM), intuitionistic fuzzy matrices (IFM) and a new operation \( * \) defined on the set \( I_{n} = \left\{ {1,2, \ldots ,n} \right\}. \) The system \( (I_{n} , * ) \) is an abelian group. This group is pivotal in our paper. Circulant intuitionistic fuzzy matrices is defined also in this paper via the group \( (I_{n} , * ) \) as a new way for defining circulant
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Integrated optimization of feeder routing and stowage planning for containerships Soft Comput. (IF 3.05) Pub Date : 2021-01-07 Mingjun Ji, Lingrui Kong, Yunxiao Guan
The sailing safety constraints of containerships were ignored in the previous studies on feeder containership routing problems; however, they are especially critical for small-sized feeder containerships. In this study, we optimize feeder routes while incorporating stowage plans to address the sailing safety of containerships. Firstly, a mixed integer nonlinear programming model for integrated optimization
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Some bipolar-preferences-involved aggregation methods for a sequence of OWA weight vectors Soft Comput. (IF 3.05) Pub Date : 2021-01-07 LeSheng Jin, Ronald R. Yager, Zhen-Song Chen, Jana Špirkovà, Daniel Paternain, Radko Mesiar, Humberto Bustince
The ordered weighted averaging (OWA) operator and its associated weight vectors have been both theoretically and practically verified to be powerful and effective in modeling the optimism/pessimism preference of decision makers. When several different OWA weight vectors are offered, it is necessary to develop certain techniques to aggregate them into one OWA weight vector. This study firstly details
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Deep learning-based investment strategy: technical indicator clustering and residual blocks Soft Comput. (IF 3.05) Pub Date : 2021-01-07 Anuar Maratkhan, Ibrakhim Ilyassov, Madiyar Aitzhanov, M. Fatih Demirci, A. Murat Ozbayoglu
Financial forecasting using computational intelligence nowadays remains a hot topic. Recent improvements in deep neural networks allow us to predict financial market behavior better than traditional machine learning approaches. In this paper, we propose three novel deep learning-based financial forecasting frameworks, all of which considerably outperform existing approaches, yielding a much better
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Toward endosymbiosis modeling using reaction networks Soft Comput. (IF 3.05) Pub Date : 2021-01-07 Tomas Veloz, Daniela Flores
Endosymbiosis is a type of symbiosis where one species inhabits another species, and both are benefited. It is not trivial to develop models of endosymbiosis because the interaction might involve complex mechanisms, consisting of various steps, and occurring at different levels of the organisms activity. Reaction networks can be applied to model complex ecological interaction mechanisms that can hardly
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Adaptive learning control synchronization for unknown time-varying complex dynamical networks with prescribed performance Soft Comput. (IF 3.05) Pub Date : 2021-01-06 Aili Fan, Junmin Li
This paper proposes a prescribed performance adaptive learning control scheme for complex dynamical networks. It can ensure that the states of all nodes in the complex dynamical networks can synchronize to the specified target trajectory, and satisfy prescribed performance constraints. Based on Lyapunov stability theory, it is proved that all signals in the closed-loop systems are bounded and the synchronization
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A novel interval-valued fuzzy soft decision-making method based on CoCoSo and CRITIC for intelligent healthcare management evaluation Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Xindong Peng, R. Krishankumar, K. S. Ravichandran
The intelligent healthcare management is of great concern to mobilize the enthusiasm of individuals and groups, and effectively use limited resources to achieve maximum health improvement by AI technology. When considering the intelligent healthcare management evaluation, the primary issues involve many uncertainties. Interval-valued fuzzy soft set, depicted by membership degree with interval form
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Dimensionality reduction to solve resource allocation problem in 5G UDN using genetic algorithm Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Adolfo Reyna-Orta, Ángel G. Andrade
5G ultra-dense network (UDN) systems consist of massive deployment of small cells. This technology allows increasing spectral efficiency and solving the spectrum scarcity problem. However, as small cell count increases, the probability of severe interference increases, causing a network capacity degradation. The resource allocation (RA) algorithms distribute the available spectrum resources with the
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Cost assessment of different SMP strategies considering network contingencies with MBSOS Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Soumesh Chatterjee
Appropriate placement of synchrophasor meters will save huge capital investment and give improved wide area monitoring, control, and protection. Being costly and having flexible channel capacity, the synchrophasor meters should be placed judiciously in the network to avoid unnecessary expenses. In this paper, the practical cost assessment of phasor measurement unit (PMU) placement has been done for
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Test case prioritization to examine software for fault detection using PCA extraction and K-means clustering with ranking Soft Comput. (IF 3.05) Pub Date : 2021-01-05 N. Gokilavani, B. Bharathi
Many software-related failures or faults were caused as the consequence of not detecting it early and prevailing constraints of time and supplies available during any software examination. Having identified the challenges in the regression software testing of any software, many have started moving their attention towards the test cases or else validation suites prioritization. In this work, we have
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Optimization of stability of humanoid robot NAO using ant colony optimization tuned MPC controller for uneven path Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Abhishek Kumar Kashyap, Dayal R. Parhi
The primary conventional method for simplifying legged robots’ complex walking dynamics involves using low-dimensional models such as the linear inverted pendulum model (LIPM). This paper emphasizes utilizing the LIPM plus flywheel model (LIPPFM) for analysis of the complete dynamic motion of the humanoid robot. Inclining toward a more realistic case, the model is improvised to remove the COM’s height
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Modeling the progression of COVID-19 deaths using Kalman Filter and AutoML Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Tao Han, Francisco Nauber Bernardo Gois, Ramsés Oliveira, Luan Rocha Prates, Magda Moura de Almeida Porto
The COVID-19 pandemic continues to have a destructive effect on the health and well-being of the global population. A vital step in the battle against it is the successful screening of infected patients, together with one of the effective screening methods being radiology examination using chest radiography. Recognition of epidemic growth patterns across temporal and social factors can improve our
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Pythagorean fuzzy points and applications in pattern recognition and Pythagorean fuzzy topologies Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Murat Olgun, Mehmet Ünver, Şeyhmus Yardımcı
In this paper, we define the concept of Pythagorean fuzzy point. We define a similarity measure between Pythagorean fuzzy points, and we give an application of this similarity measure in pattern recognition. We also introduce a new type of continuity for the functions defined between two Pythagorean fuzzy topological spaces. Moreover, we introduce the concept of Moore–Smith convergence in Pythagorean
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An improved differential evolution algorithm and its application in optimization problem Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Wu Deng, Shifan Shang, Xing Cai, Huimin Zhao, Yingjie Song, Junjie Xu
The selection of the mutation strategy for differential evolution (DE) algorithm plays an important role in the optimization performance, such as exploration ability, convergence accuracy and convergence speed. To improve these performances, an improved differential evolution algorithm with neighborhood mutation operators and opposition-based learning, namely NBOLDE, is developed in this paper. In
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A new evolving mechanism of genetic algorithm for multi-constraint intelligent camera path planning Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Zeqiu Chen, Jianghui Zhou, Ruizhi Sun, Li Kang
The main goal of intelligent camera path planning is to determine an optimal pathway that proceeds from the starting position to the target position under several constraint conditions in the given environment. Genetic algorithm-based method has found wide application in path optimization problem in the intelligent camera community recently. Because the roaming environments are very complex, the planning
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Optimal placement of different types of DG units considering various load models using novel multiobjective quasi-oppositional grey wolf optimizer Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Sajjan Kumar, Kamal Krishna Mandal, Niladri Chakraborty
The optimal placement of Distributed Generation (DG) units in radial distribution system is one of the important ways for techno-economic improvements. The maximum technical benefits can be extracted by minimizing the distribution power loss as well as bus voltage deviation, whereas the maximum economical benefits can be procured by minimizing the total yearly economic loss which includes installation
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A duality for two-sorted lattices Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Umberto Rivieccio, Achim Jung
A series of representation theorems (some of which discovered very recently) present an alternative view of many classes of algebras related to non-classical logics (e.g. bilattices, semi-De Morgan, Nelson and quasi-Nelson algebras) as two-sorted algebras in the sense of many-sorted universal algebra. In all the above-mentioned examples, we are in fact dealing with a pair of lattices related by two
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Cross-modality co-attention networks for visual question answering Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Dezhi Han, Shuli Zhou, Kuan Ching Li, Rodrigo Fernandes de Mello
Visual question answering (VQA) is an emerging task combining natural language processing and computer vision technology. Selecting compelling multi-modality features is the core of visual question answering. In multi-modal learning, the attention network provides an effective way that selectively utilizes the given visual information. However, the internal relationship of modalities is often ignored
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Risk evaluation model for failure mode and effect analysis using intuitionistic fuzzy rough number approach Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Guangquan Huang, Liming Xiao, Genbao Zhang
Failure mode and effect analysis (FMEA) is a multidisciplinary team-based reliability analysis tool used in a wide range of industries. However, the conventional FMEA technique has been criticized for some important deficiencies regarding risk assessments, the weights of experts and risk factors, and risk priority. Although numerous fuzzy-based modified FMEA models have been developed to improve the
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An efficient solution of nonlinear enhanced interval optimization problems and its application to portfolio optimization Soft Comput. (IF 3.05) Pub Date : 2021-01-05 P. Kumar, A. K. Bhurjee
A general optimization problem whose parameters and decision variables are intervals, is known as an enhanced interval optimization problem. This article has focused on nonlinear enhanced interval optimization problem. Here, a methodology is derived to determine the efficient solutions of this problem. Theoretical justification for the existence of the solution to this problem is discussed. In this
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A two-step trace model for the detection of UVI attacks against power grids in the wireless network Soft Comput. (IF 3.05) Pub Date : 2021-01-05 R. B. Benisha, S. Raja Ratna
Due to the extensive development of information transmission in the SCADA power grids, securing the network has become more challenging for guaranteed measurements and transformations. An ultraviolet injection attack (UVI) is infused with malicious data and obstruct in planning the centers that cause a high reduction in the power grids. To overcome this problem, two-step trace model is used that includes
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Empirical distribution-based framework for improving multi-parent crossover algorithms Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Zhengkang Zuo, Lei Yan, Sana Ullah, Yiyuan Sun, Ruihua Zhang, Hongying Zhao
Multi-parent crossover algorithms (MCAs) are widely used in solving optimization problems in many fields relying on encoding, crossover, variation and choice operators to produce iterative offspring chromosome. In this paper, a real-coded schema to support this genetic optimization process is considered. At each crossover stage, a linear combination of coefficients at the same scale hybridizes a fixed
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Multi-criteria decision making process based on some single-valued neutrosophic Dombi power aggregation operators Soft Comput. (IF 3.05) Pub Date : 2021-01-05 Chiranjibe Jana, Madhumangal Pal
The single-valued neutrosophic sets (SVNs) have a lot of applications in the field of engineering and scientific problems. In this paper, the Dombi operations and power averaging operator is used to constructing some single-valued neutrosophic Dombi power operators, i.e., single-valued neutrosophic Dombi power weighted averaging (SVNDPWA) operator, single-valued neutrosophic Dombi power order weighted
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A hybrid chaotic map with coefficient improved whale optimization-based parameter tuning for enhanced image encryption Soft Comput. (IF 3.05) Pub Date : 2021-01-05 S. Saravanan, M. Sivabalakrishnan
The security of the data becomes the main concern due to the quick rise in the exchange of data over the open networks and the Internet. The cryptographic techniques based on chaos theory reveal some novel and effectual orders to develop secure image encryption approaches. Images are the most attractive kinds of data in the encryption domain. In current years, the chaos-based cryptographic techniques
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