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

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

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

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

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

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

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

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

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

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

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

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

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

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

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”.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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