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In recommendation algorithms, data sparsity and cold start problems are inevitable. To solve such problems, researchers apply auxiliary information to recommendation algorithms, mine users’ historical records to obtain more potential information, and then improve recommendation performance. In this paper,...

The aim of this paper is to provide a multiple attribute group decision making (MAGDM) method based on the 2-dimension linguistic weight Bonferroni mean aggregation (2DLWBMA) operator. Firstly, the new operations of 2-dimension linguistic variables are defined. Then, the 2-dimension linguistic Bonferroni...

Leukemia cancer, like other types of cancer, is a deadly health condition that threatens the lives of many people around the world. Micro array data are used extensively to reveal the gene-cancer as well as gene–gene relationships of Leukemia cancer due to the fact that it allows the expression value...

In this essay, we investigate the probabilistic linguistic multiple attribute group decision making (PL-MAGDM) with incomplete weight information. In this method, the linguistic representation developed recently is converted into probabilistic linguistic information. For deriving the weight information...

We devote to study the arithmetic operator of fuzzy regular prismoid numbers as well as the degree of similarity between fuzzy regular prismoid numbers, and then the arithmetic operator and the degree of similarity are applied in risk analysis. Firstly, the arithmetic operator of fuzzy regular prismoid...

Multi-criteria decision-making is a daily process in everyday life, in which different alternatives are evaluated over a set of conflicting criteria. Decision-making is becoming increasingly complex, and the apparition of uncertainty and vagueness is inevitable, especially when related to sustainability...

In the fashion market, the lack of historical sales data for new products imposes the use of methods based on Stock Keeping Unit (SKU) attributes. Recent works suggest the use of functional data analysis to assign the most accurate sales profiles to each item. An application of siamese neural networks...

Using the theory of monads in categories and the theory of monadic relations, the concept of general transformation operator defined by a monadic relation is introduced. It is proven that a number of standard relations used in categories of fuzzy structures are monadic relations for monads defined in...

The challenges faced in underwater communication systems are limited bandwidth, Energy consumption rate, larger propagation delay time, End-End Delay (E-ED), 3D topology, media access control, routing, resource utilization and power constraints. These issues and challenges are solved by means of deploying...

This paper studies numerical solutions for fuzzy initial value problems, where the initial conditions are given by interactive fuzzy numbers. The fuzzy solution is given by a numerical method that employs the arithmetic of interactive fuzzy numbers and yields a fuzzy number at each instant of time. The...

Fuzzy graph models are present everywhere from natural to artificial structures, embodying the dynamic processes in physical, biological, and social systems. As real-life problems are often uncertain on account of inconsistent and indeterminate information, it seems very demanding for an expert to model...

Accurate daily precipitation prediction is crucially important. However, it is difficult to predict the precipitation accurately due to inherently complex meteorological factors and dynamic behavior of weather. Recently, considerable attention has been devoted in soft computing-based prediction approaches....

Cancer is a fatal disease that is continuously growing in the developed countries. It is also considered as a main global human health problem. Based on several studies, which have been conducted so far, we found out that Hybrid Particle Swarm Optimization and Artificial Bee Colony Algorithm has never...

The water–energy–food (W-E-F) nexus approach has become the basis for a host of many methods addressing the security of global resources, whose methods are often nonparametric, due to the complex and indefinable relationship among the three. In this work, the nonparametric evaluation method data envelopment...

The reliability of a dynamic system is not constant under uncertain random environments due to the interaction of internal and external factors. The existing researches have shown that some complex systems may suffer from dependent failure processes which arising from hard failure and soft failure. In...

There are many challenges in accurately measuring cigarette tar constituents. These include the need for standardized smoke generation methods related to unstable mixtures. In this research were developed algorithms using fusion of artificial intelligence methods to predict tar concentration. Outputs...

Vendor-managed inventory (VMI) is a supply chain coordination improvement system. Due to the vendor’s responsibility for the replenishment decision, demand forecasting and quick response for retailers’ demand fluctuations are crucial in a VMI system. Our study focuses on order prediction of the VMI for...

Classification in artificial intelligence is usually understood as a process whereby several objects are evaluated to predict the class(es) those objects belong to. Aiming to improve the interpretability of predictions resulting from a support vector machine classification process, we explore the use...

Neighborhood rough set is a powerful tool to deal with continuous value information systems. Graphics processing unit (GPU) computing can efficiently accelerate the calculation of the attribute reduction and approximation sets based on matrix. In this paper, we rewrite neighborhood approximation sets...

Websites are considered as the core infrastructure of e-government, so evaluating the quality of websites assists organizations to provide high-quality online services to citizens. For this purpose, this paper is seeking to design a model that enables any organization to evaluate the quality of its websites...

The notions of complex q-rung orthopair fuzzy sets (Cq-ROFSs) and linguistic sets (LSs) are two different concepts to deal with uncertain information in multi-attribute group decision-making (MAGDM) problems. The Heronain mean (HM) and geometric Heronain mean (GHM) operators are an effective tool used...

The objective of this paper is to establish the relationship between L-valued approximation spaces and L-valued transformation systems. We show that for each L-valued upper/lower fuzzy transformation system there exist an L-valued reflexive approximation space and vice versa. In between, we study the...

The multi-unmanned aerial vehicle (UAV) must autonomously perform reconnaissance-attack-evaluation tasks under multiple constraints in the battlefield environment. This paper proposes a nearest neighbor method designed with the shortest neighboring distance as an indicator which quickly solves the optimal...

In this paper, we evaluate the development level of internet finance by focusing on three major virtual economies, internet “Baby” fund, internet financial credit and Shanghai Composite Index for the first time. We examine the disequilibrium relations between the development of both internet finance...

Wood species recognition is an important work in the wood trade and wood commercial activities. Although many recognition methods were presented in recent years, the existing wood species recognition methods mainly use shallow recognition models with low accuracy and are still unsatisfying for many real-world...

In this paper, game-theoretic optimization by particle swarm optimization (PSO) is used to determine the Nash equilibrium value, in order to resolve the confusion in choosing appropriate bidders in multi-round procurement. To this end, we introduce an approach that proposes (i) a game-theoretic model...

In order to solve the shortcomings of the existing mathematical expressions of the user's personalized recommendation search and to increase the accuracy of the user's personalized information recommendation, in this study, the collaborative filtering algorithm, the related theory of fuzzy...

This research investigates how to properly place garment industry workers to work stations in the assembly line to achieve a more balanced production and to reduce the production cycle time. We simulate the assembly line balancing problem via staff assignments. In our research, we conduct a comparative...

During last two decades, power adaptation and beamforming solutions have been proposed for multiple input multiple output (MIMO) Ad Hoc networks. Game theory based methods such as cooperative and non-cooperative joint beamforming and power control for the MIMO ad hoc systems consider the interference...

Spherical fuzzy sets, originally proposed by F.K. Gündogdu, C. Kahraman, Spherical fuzzy sets and spherical fuzzy TOPSIS method, J. Intell. Fuzzy Syst. 36 (2019), 337–352, can handle the information of type: yes, no, abstain and refusal, owing to the feature of broad space of admissible triplets. This...

Object detection and distance estimation based on videos are important issues in advanced driver-sssistant system (ADAS). In practice, fisheye cameras are widely used to capture images with a large field of view, which will produce distorted image frames. But most of the object detection algorithms were...

Growing use of social media such as Twitter, Instagram, Facebook, etc., by consumers leads to the vast repository of consumer generated data. Collecting and exploiting these data has been a great challenge for clothing industry. This paper aims to study the impact of Twitter on garment sales. In this...

Attribute reduction is a hot topic in the field of data mining. Compared with the traditional methods, the attribute reduction algorithm based on covering rough set is more suitable for dealing with numerical data. However, this kind of algorithm is still not efficient enough to deal with large-scale...

We study the influence of fuzziness of trapezoidal fuzzy sets in the strong fuzzy partitions (SFPs) that constitute the database of a fuzzy rule-based classifier. To this end, we develop a particular representation of the trapezoidal fuzzy sets that is based on the concept of cuts, which are the cross-points...

Imbalance learning is a challenging task for most standard machine learning algorithms. The Synthetic Minority Oversampling Technique (SMOTE) is a well-known preprocessing approach for handling imbalanced datasets, where the minority class is oversampled by producing synthetic examples in feature vector...

The different face regions have different degrees of importance for face recognition. In previous Hausdorff distance (HD) measures, points are treated as same importance, or weight different points that calculated from gray domain. In this paper, a new weighting function of HD based on the eigenface...

One of the current trends in the deep neural network technology consists in allowing a man–machine interaction and providing an explanation of network design and learning principles. In this direction, an experience with fuzzy systems is of great support. We propose our insight that is based on the particular...

It is well known that convexity and nonconvexity develop a strong relationship with different types of integral inequalities. Due to the importance of the concept of nonconvexity and integral inequality, in this paper, we present some new classes of preinvex fuzzy-interval-valued functions involving...

Knowledge on pedestrian behavior is the basis to build decision support system for crowd evacuation management in emergency. In this paper, the impact of paired walking behavior on pedestrian counter flow in a channel is studied. The pedestrian walking behaviors are simulated by the cellular automaton...

Face authentication has been widely used in personal identification. However, face authentication systems can be attacked by fake images. Existing methods try to detect such attacks with different features. Among them, using color images become popular since it is flexible and generic. In this paper,...

A large number of fatalities are caused by the vehicle-pedestrian accidents. Under a potential conflict between the vehicle and jaywalking pedestrian, giving precedence to the pedestrian will be a proper decision taken by the driver to avoid collision. Field traffic data has been collected by video recording...

As a powerful extension to hesitant fuzzy sets (HFSs), dual hesitant fuzzy sets (DHFSs) have been closely watched by many scholars. The DHFSs can reflect the disagreement and hesitancy of decision-makers (DMs) flexibly and conveniently. However, all the evaluation values under the same membership degree...

In order to complete the task of the woodland census in Chenzhou, China, this paper carries out a remote sensing survey on the terrain of this area to produce a data set, and used deep learning methods to label the woodland. There are two main improvements in our paper: Firstly, this paper comparatively...

Solving complex informal problems using spatial data is often used in industry and business. In the absence of a solution algorithm, analyst resorts to a heuristic search for a solution, which is based on an interactive dialogue with a geographic information system (GIS). The analyst builds a cartographic...

Intelligent traffic control is influenced by Stretching-segment design, parameters optimization of traffic control have to consider saturation flow rate in approach. Many intersections with different stretching-segment design forms are selected to study on saturation flow rate at peak rush hour and ordinary...

Recommender systems have played a relevant role in e-commerce for supporting online users to obtain suggestions about products that best fit their preferences and needs in overloaded search spaces. In such a context, several authors have proposed methods focused on removing the users' inconsistencies...

High-Efficient traffic system is very important for economy and society of cities. Previous studies on the traffic comparison mostly took a city as a whole, but ignored the differences among areas inside the city. But in fact, the traffic congestion in different areas with a city is mostly different....

We show that the convergence proof of a recent algorithm called dist-EF-SGD for distributed stochastic gradient descent with communication efficiency using error-feedback of Zheng et al., Communication-efficient distributed blockwise momentum SGD with error-feedback, in Advances in Neural Information...

The reasoning ability of the belief rule-based system is easy to be weakened by the quality of training instances, the inconsistency of rules and the values of parameters. This paper proposes an ensemble approach for extended belief rule-based systems to address this issue. The approach is based on the...

The traffic lights play an indispensable role in urban road safety and researches on intelligent vehicles become more popular recently. In this paper an automatic system for robust and real-time detection and recognition of traffic lights for intelligent vehicles based on vehicle-mounted camera is proposed....