Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Hu, Yun | Zhou, Zuojian | Hu, Kongfa | Li, Hui

Article Type: Research Article

Abstract: Detecting community structure is critical in analysing social networks which are flourishing and influencing every aspect of people’s social life. Most social network systems are composed with complicated entity relations such and social interests, user relationships and their interactions. To understand how users interact with each other under the community level, its not enough to consider one kind of these relations while ignore the other. An united network model that can comprehensively integrate these relations is essential for community detection. Focusing on such kind of problem when dealing with social network with multiple relations, this paper proposes a heterogeneous network …model which characterizes and constructs user similarity relations by combining both of users’ interests and their interactions attributes. Based on the heterogeneous similarity model, an additive spectral decomposition algorithm is applied to detect overlapped communities from the network. The remarkable effect of our heterogeneous model is the ability to reveal most important attributes of the blog network. And, comparing to crisp clustering method, the additive spectral decomposition algorithm proposed is effective for finding overlapped user groups which is more reasonable among social networks where users tend to join multiple social groups. Results of experimental studies on real-world and synthetic datasets demonstrate the effectiveness of the algorithm with respect to the size, the distributive structure and the high dimensionality of the datasets. Show more

Keywords: Community detection, micro blog network, user interest, user interaction, heterogeneous network model, user similarity modelling

DOI: 10.3233/JIFS-179415

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Liu, Hui | Li, Yifan | Hong, Rui | Li, Zhenming | Li, Ming | Pan, Wei | Glowacz, Adam | He, Hao

Article Type: Research Article

Abstract: In order to trace the research trends and hotspots related to the field of driver behavior research both in China and worldwide, a bibliometric analysis was performed to systematically analyze 7208 scientific papers about driver behavior in the Web of Science database from 1957 to 2018, and the results were discussed from the 6 perspectives of growth trends of publications, geographical distribution, subject categories, institutions, authors and keywords distribution. The results show that research on driver behavior has been increasing rapidly since the 1990 s, but research in Europe and the United States started more than 20 years earlier than in …China. Currently, transportation, engineering, computer science and behavioral science have replaced the traditional subject categories, becoming the most important domains in this field. Research on driver behavior focuses on safety and systems using simulation models which is interacted with almost everything concerning traffic operation and safety. The current trend is that more researchers are working on understand the driver-vehicle-system interactions under the environment of connected and autonomous vehicle. Further research is needed to focus on unsafe driving behavior based on driver-vehicle-system interactions. This study will provide scholars in related academia and industry with panoramic knowledge of driver behavior research, as well as research hotspots and future research directions. Show more

Keywords: Driver behavior, research trends, driving safety, knowledge graph, visualization

DOI: 10.3233/JIFS-179424

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2019

Authors: Han, Hongmu | Dong, Xinhua | Zuo, Cuihua

Article Type: Research Article

Abstract: Recommender systems are widely used to provide users with items they may be interested in without explicitly searching. However, they suffer from low accuracy and scalability problems. Although existing clustering techniques have been incorporated to solve these inherent problems, most of them fail to achieve further improvement in recommendation accuracy because of ignoring the correlations between items and the different effects of item attributes on recommendation results. In this article, we propose a novel recommendation algorithm to alleviate these issues to a large extent. First of all, users and items are clustered into multiple cluster subsets based on user-item rating …matrix and item attribute deriving from domain experts, respectively. Then we use a selection method relying on item attribute to mine candidate items and only their predictions will be calculated in the next step, which can save the computation time greatly. Furthermore, by weighting the predictions with TF-IDF (Term Frequency-Inverse Document Frequency) weights, the top-N recommendations are generated to the target user for return. Finally, comparative experiments on two real datasets demonstrate that this algorithm provides superior recommendation accuracy in terms of MAE (Mean Absolute Error) and RMSE (Root Mean Square Error). Show more

Keywords: Recommender systems, clustering, item attribute, weight, recommendation accuracy

DOI: 10.3233/JIFS-179418

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Huang, Jun | Zhuo, Yumin | Tian, Xuemei | Zhu, Dingju | Mustafa, Rashed

Article Type: Research Article

Abstract: Conventional method for disease treatment plan relies too much on the subjective experience and theoretical knowledge of the doctor or experts. Uncertain decisions of the doctor or experts may be suggested wrong treatment plan. This paper provides a treatment suggestion system based on big data and knowledge base no longer relies on the subjective experience of the doctor, but relies on the objective historical data of treatment cases including disease information, personal information, treatment plan and treatment effect score. The suggested treatment plan is much more targeted and reliable, thereby assisting the doctor to determine the disease treatment plan more …quickly, accurately and reasonably. Show more

Keywords: Disease treatment plan, big data, knowledge base

DOI: 10.3233/JIFS-179425

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Yörükoğlu, Mehmet | Aydın, Serhat

Article Type: Research Article

Abstract: The Industrial Revolution, which started with steam machines, has evolved into intelligent systems in which objects speak to each other in the name of Industry 4.0. Smart containers (SC), which are the latest in this evolution of containers and one of the key elements of logistic in Supply Chain Management System (SCMS), stand out with their flexibility, traceability, and contribution to the optimization of the supply chain. In this paper the existing properties of the currently evolving smart containers are compiled and the users’ needs that will guide future designs are determined. In the application section, three different smart containers …are evaluated according to seven different conflicting criteria in neutrosophic environment. By using neutrosophic TOPSIS method relative closeness coefficient of alternatives are calculated. Finally alternatives are ranked in descending order. The originality of the paper is that smart containers evaluation problem is handled by the neutrosophic MCDM method for the first time in the literature. Show more

Keywords: Industry 4.0, smart container, multi criteria decision making, neutrosophic TOPSIS

DOI: 10.3233/JIFS-179444

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Wang, Yuanyuan | Wang, Zhijian | Jiang, Mingxin | Chen, Liqi | Shen, Tianhao | Zhang, Wenyang

Article Type: Research Article

Abstract: Person re-identification (ReID) is a critical work in the field of intelligent image processing and deep learning, which has attracted the attention of industry application. Person ReID focuses on matching person images obtained from non-overlapping camera views and finding the person-of-interest. An important unresolved problem is to obtain efficient metric for measuring the similarity among pedestrian images. Lately, deep learning with metric learning has become a general method for person ReID. Yet, previous methods mainly used a variety of distance to measure the similarity among samples. The way of distance measure is more sensitive when the scale changes. In this …paper, we propose angular loss with hard sample mining (ALHSM) to learn better similarity metric for the person ReID. Our work uses the angular relationship in triangles as a measure of similarity, minimizing the angle at the negative point of the triangle. ALHSM combines with hard negative mining strategies, which learn better similarity metric and achieve advanced performance on several benchmark datasets. The experimental results show that our work is competitive compared to the state-of-the-art. Show more

Keywords: Person re-identification, deep learning, angular loss, intelligent image processing

DOI: 10.3233/JIFS-179416

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Btissam, Zerhari | Ayoub, Ait Lahcen | Salma, Mouline

Article Type: Research Article

Abstract: Attribute and class noises are the two important sources of Corruptions (noise) contained in real-world datasets which may deteriorate data interpretation and accuracy. Class noise has potentially serious negative impacts compared to attribute noise, however, the existing major class noise detection methods are not able to address this problem efficiently. To overcome issues related to detection and the elimination of class noise, we suggest a new noise filtering approach able to identify and remove class noise, called Multi-Iterative Partitioning Class Noise Filter (MIPCNF). Since there is no single filter that consistently outperforms its counterparts in all database types and in …different levels of noise, our approach relies on an algorithm in which several rounds of class noise detection are performed on different partitions of the data using several classifiers. Therefore, we use different filtering strategies: iterative noise filter, partitioning filter and ensemble-based filter. The experimental results, on 14 real-world datasets, and statistical analysis, show that our method is not only overcoming the higher noise but also over-performing latest class noise detection and elimination strategies in different levels of noise. Show more

Keywords: Class noise, Noise Detection, Noise Elimination, Partitioning Filter, Large Data

DOI: 10.3233/JIFS-190261

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Labella, Álvaro | Rodríguez, Rosa M. | Martínez, Luis

Article Type: Research Article

Abstract: Group Decision Making (GDM) deals with decision problems in which multiple experts, with their own attitudes and knowledge, evaluate different alternatives or solutions with the aim of achieving a common solution. In such cases disagreements can appear, which might led to failed solutions. To manage such conflicts, Consensus Reaching Processes (CRPs) have been added to the GDM solving process. GDM problems under uncertainty often model uncertainty by linguistic descriptors, being most of linguistic based CRPs based on the use of single linguistic terms for modelling experts’ opinions, which cannot be expressive enough in some situations because of either the uncertainty …involved or the experts’ hesitancy. Therefore, this paper aims to fill this gap by proposing a novel consensus model dealing with GDM problems in which experts’ preferences are elicited by means of Comparative Linguistic Expressions (CLEs) based on Hesitant Fuzzy Linguistic Term Sets, which allow to model the experts’ hesitancy in a flexible way. Furthermore, CLEs are modelled by fuzzy membership functions in order to keep the fuzzy representation in the whole CRP and preserve as much information as possible. Additionally, the proposed model is implemented and integrated in an intelligent CRP support system, so-called AFRYCA 3.0 to carry out a case study about this new CRP and compare it with previous models. Show more

Keywords: group decision making, comparative linguistic expressions, hesitant fuzzy linguistic term sets, consensus reaching process

DOI: 10.3233/JIFS-179445

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Bayram, Mehmet | Akat, Muzaffer | Bulkan, Serol

Article Type: Research Article

Abstract: Pairs trading is a widespread market-neutral trading strategy aiming to utilize the relationship between pairs of financial instruments in efficient markets, where predictability of separate asset movements is theoretically not possible. The implication of trading pairs, following statistical analysis, is to buy the underpriced asset while short selling the overpriced. The predicted price relationship is determined through analysis of historical spread data between the members of the corresponding pair. The investor expects the price difference, in an efficient market, should converge and stocks return to their ‘fair value’, where the positions are closed and profit is realized. The main focus …of this study is the contribution of the fuzzy engine to the existing pairs trading strategy. Widespread classical ‘crisp’ technique is chosen, utilized and compared with the developed ‘fuzzy’ model throughout the paper. In order to further improve this contribution, the expert opinions extracted from the Bloomberg database are also integrated into the fuzzy decision-making process. In most studies, transaction costs are simply ignored. As a final robustness check, the transaction costs are also considered. The improvement reached by the developed fuzzy technique is observed to be even more remarkable in this case. Show more

Keywords: pairs trading, algorithmic trading, fuzzy statistical arbitrage

DOI: 10.3233/JIFS-179442

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Wang, Yang | Zhang, Shengyu | Cen, Hongjie | Zou, Bo

Article Type: Research Article

Abstract:  The explosive growth of wireless data services, especially more and more requirement for high-definition videos, demands higher capacity of future wireless communication systems to meet this trend. One efficient solution to this problem is to improve the spectral efficiency. This paper analyzes the basic principles of large-scale antenna array system, whose performance is verified by simulation. Key technologies on large-scale antenna array system, such as channel state information acquisition, antenna array design, code book design, are also studied. The results show that large-scale antenna array system can greatly improve spectral efficiency and reduce system energy consumption.

Keywords: Large-scale antenna array system, massive MIMO, spectral efficiency, interference mitigation

DOI: 10.3233/JIFS-179422

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Wang, Yajun | Sun, Fuming | Li, Xiaohui

Article Type: Research Article

Abstract:  To reduce and eliminate the three problems for large-scale data sets that include high computational complexity, large storage space, and long time-consuming in complex batch process with inherent dynamics and nonlinearity, a novel approach based on multi-dynamic kernel principal component analysis (MDKPCA) by exploiting compound dimensionality reduction for fault detection is proposed. The method firstly uses discrete cosine transform (DCT) having strong energy aggregation and distance preserving property to realize dimensionality reduction without changing the essential characteristics of data. Then after the reduced dimension data is processed by inverse transformation, the dynamic kernel principal component analysis (DKPCA) model is established …by combining the autoregressive moving average time series (ARMAX) model and kernel principal component analysis (KPCA) to handle the nonlinearity and dynamics in industrial process. Finally, one penicillin fermentation process case for fault monitoring is provided to test the effectiveness of the proposed method, where the comparison with multiway kernel principal component analysis (MKPCA) results is covered. Show more

Keywords: Compound dimensionality reduction, discrete cosine transform, multi-dynamic kernel principal component analysis, large-scale data set, penicillin fermentation process

DOI: 10.3233/JIFS-179421

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Wu, Shaofei

Article Type: Research Article

Abstract: We propose models based on SVM, Naïve Bayes and deep learning to solve the consumption intention classification problem. Applying consumption intention mining to prediction tasks in social media. This paper discusses consumption intention towards a certain kind of product, i.e. movie, and uses movie consumption intention as an important feature in box office prediction. We combine consumption intention with traditional features used in the problem of box office prediction, and achieve a outperforms previous work of this problem We build a system based on linear regression which automatically predicts movies’ total box office and opening weekend box office one day …prior to the movie’s release date. Show more

Keywords: Text intention mining, SVM, deep learning

DOI: 10.3233/JIFS-179423

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Flores-Martínez, M.-A. | Osorio-Gordillo, G.-L. | Vargas-Méndez, R.-A. | Reyes-Reyes, J.

Article Type: Research Article

Abstract: This paper presents an algorithm for the design of a Generalized Dynamic Functional Observer (GDFO) for Takagi-Sugeno systems. A set of conditions are provided for the existence of the observer, which can be applied to the proportional functional observer that is presented as a particular case of the proposed generalized observer. Lyapunov function is used to find stability condition of the observer. Stability conditions are given in terms of linear matrix inequalities (LMIs). A glucose-insulin system example illustrates the performance and effectiveness of the proposed approach.

Keywords: Generalized dynamic functional observer, Takagi-Sugeno systems, glucose-insulin system, feedback control

DOI: 10.3233/JIFS-182872

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Meng, Xiao-Li | Gong, Liu-Tang | Yao, Jen-Chih

Article Type: Research Article

Abstract:   Evaluating the performances of a set of entities called decision making units (DMUs) which convert multiple inputs into multiple outputs has long been considered as a difficult task because one is dealing with complex economic. This work proposes an inequality approach to evaluate the performances of DMUs. Inequalities consist of expressions of the production possibility set and the line segments joining the evaluated DMU to the positive output-axes. However, in real-world application involving performance measurement, inputs and outputs are often imprecise and fluctuated. In this case, a fuzzy inequality approach is proposed to evaluate the performances. What is more, …fuzzy relative efficiency is dependent upon the number of solutions. Furthermore, the minimal element is used to distinguish the fuzzy relative efficient DMUs. Finally, two numerical examples are used to illustrate the fuzzy approach and compare the results with those obtained with alternative fuzzy approaches. Show more

Keywords: Fuzzy data envelopment analysis, Fuzzy inequality, The production possibility set, The positive output-axes, Minimal element

DOI: 10.3233/JIFS-182823

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Saritha, S. | Santhosh Kumar, G.

Article Type: Research Article

Abstract: The spatial colocation problem is totally different from the traditional association rule problem, as it operates on spatial data and not on conventional transaction data. In this work, a spatial colocation mining framework is proposed that mines spatial colocation of image-objects present in images using a tensor factorization approach. The framework takes in image data directly, tensorize it and perform the mining task, thus eliminating the need of converting into a transaction based approach. An interestingness measure called, spatial dominance is also proposed in this work. This measure is an indicator of the prevalence of the mined colocation pattern. Algorithms …are designed in this framework, first to map the classified pixels as members of image-objects, which is a pre-stage before mining and second to find spatial colocation patterns. Experiment results are provided to show the strength of the spatial colocation mining algorithm. Show more

Keywords: Data mining, spatial colocation, tensors, image-objects

DOI: 10.3233/JIFS-190122

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Lei, Guoping | Luo, Xiuying | Cai, Li | Gao, Le | Dai, Nina | Xu, Qingshan | Tan, Zefu

Article Type: Research Article

Abstract: Battery management system (BMS) is an important part of electric vehicle that can improve the efficiency of battery and ensure the safety during operating process. State of charge (SOC) estimation is one of kernel technology of BMS. High precision of SOC estimation can not only increase service life of battery, but also enhance energy utilization efficiency and cut down the operational cost. Based on fully understand working principle of battery, three-order RC equivalent circuit is chose to simulate the external characteristics. Introduce the working theory of that combination of extended Kalman filter (EKF) and open circuit voltage (OCV), and the …whole recursive algorithm of estimation SOC, using the OCV-SOC look-up table to solve the problem of initial value of SOC to a certain degree. The hardware circuit and software of BMS are designed. Hardware circuit consists of current measurement circuit, voltage measurement circuit, temperature measurement circuit and equalization circuit. The software is designed by C as the development language, the Microsoft Visual Studio 2008 as development environment and SQL Server 2008 as database management system. The experiments are carried out after the experimental platform of system hardware and software is constructed. The system realizes the real-time online monitoring of BMS, SOC estimation and etc. The result verifies the reliability and feasibility. The precision requirement of SOC estimation by using EKF algorithm and OCV-SOC look-up table meets the national standard for electric vehicle. Show more

Keywords: Electric vehicle, battery management system, smart EFK algorithm, extended kalman filter, state of charge

DOI: 10.3233/JIFS-179400

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Wu, Ling | Zhao, Weihua | Zhu, Tong | Liu, Haoxue

Article Type: Research Article

Abstract: Previous studies lack a comprehensive evaluation model that combined the subjective perception of the driver and the objective driving environment. This work investigates the characteristics of drivers’ behavior risk in highway extra-long tunnels. Real-vehicle tests were conducted in two typical extra-long tunnels and the speed of skilled and unskilled drivers were collected simultaneously. The quantified model of drivers’ behavior risk was proposed based on the safety speed difference. The variation characteristics of behavior risk both inside the tunnel and ordinary highway were analysed. Further, the NARX neural network was used to predict real-time speed with the heart rate regarded as …the input variable. Results showed that skilled drivers showed the highest behavior risk in the internal zone, while the highest value of unskilled drivers was at the exit zone in the tunnel section. Both two types of drivers presented the highest and the lowest behavior risk on the ordinary highway and the tunnel entrance zone respectively. The proposed NARX model could predict synchronous speed with high accuracy. These results of the present study concern the driver’s risk characteristics in Internet of Vehicles and how to establish the automated driver model in the simulation driving environment. Show more

Keywords: Time-series modelling, NARX neural network, driver, behavior risk characteristics, safety speed difference

DOI: 10.3233/JIFS-179395

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Li, Zhao | Song, Yi | Gong, Guoqiang | Zhou, Siwei | Lv, Ke

Article Type: Research Article

Abstract: Fault localization is the critical but most expensive step in testing manufacturing software, effectively locating faults has become an increasingly concerned study. The existing spectrum-based fault localization techniques utilize spectrum information and specific prioritization algorithm to generate the suspiciousness as well as the ranking of statements. However, the effectiveness of fault localization in manufacturing software would be dramatically reduced once the statement involving bug is assigned with the same suspiciousness as other non-faulty statements. A multi-technique fusion approach (FA) is proposed based on suspicious rankings, which merges various of randomly selected fault localization techniques to minimize the difference between the …numbers of statements that need to be examined (GAP) to find the bug respectively in the worst and best assumptions, further improve the effectiveness of fault localization. In addition, a novel metric for comparing fault localization techniques is developed. Experiments on Siemens Suite shows that our approach outperforms these selected techniques in the effectiveness. Show more

Keywords: Fault localization, manufacturing software, spectrum information, multi-technique fusion, GAP

DOI: 10.3233/JIFS-179397

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Holdon, Liviu-Constantin

Article Type: Research Article

Abstract: In this article, we put forward the concepts of nodal and conodal ideals in a residuated lattice and study some properties. We state some examples and theorems. We investigate the inverse image of a nodal (conodal) ideal under a homomorphism. In addition, we pay attention to the relationships with the other types of ideals and special sets in varieties of residuated lattices. At the same time, we give a characterization of nodal ideals in terms of congruences and we show that if L is an MTL-algebra and I is a non-principal nodal ideal, then L /I is …a chain. We propose a characterization for Boolean residuated lattices (L is a Boolean residuated lattice if and only if L is an involution semi-G-agebra) and we discuss briefly the applications of our results in varieties of residuated lattices. Finally, we introduce the concept of a fuzzy (nodal) ideal of a residuated lattice, and give some related results. After that we define the concept of fuzzy ideal of a residuated lattice with respect to a t-conorm briefly, S-fuzzy ideals and we prove Representation Theorem in residuated lattices. Show more

Keywords: Residuated lattice, obstinate ideal, implicative ideal, nodal ideal, conodal ideal

DOI: 10.3233/JIFS-190297

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2019

Authors: Li, Honghui | Lu, Hailiang | Fu, Xueliang

Article Type: Research Article

Abstract: With the rapid development of data center network, the traditional traffic scheduling method can easily cause problems such as link congestion and load imbalance. Therefore, this paper proposes a novel dynamic flow scheduling algorithm GA-ACO (Genetic Algorithm and Ant COlony algorithms). GA-ACO algorithm obtains the global perspective of the network under the SDN (Software defined network) architecture. It then calculates the global optimal path for the elephant flow on the congestion link, and reroutes it. Extensive experiments have been executed to evaluate the performance of the proposed GA-ACO algorithm. The simulation results show that, in comparison with ECMP and ACO-SDN …algorithm, GA-ACO can not only reduce the maximum link utilization, but also improve the bandwidth effectively. Show more

Keywords: Data center network, SDN, elephant flow scheduling, genetic algorithm, ant colony algorithm

DOI: 10.3233/JIFS-179399

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Agarwal, Shikha | Dhyani, Akshay | Ranjan, Prabhat

Article Type: Research Article

Abstract: High dimensional data have brobdingnagian number of features, but not all features are useful. Irrelevant and redundant features may even reduce the classification accuracy. Feature selection is a process of selecting a subset of relevant features to decrease the dimensionality of data. When applied on high dimensional datasets (Big Data) the feature selection methods perceives many challenges and it is pertinent to come up with the new methods or revamp the existing methods. In this study, a new method ‘Newtonian particle swarm optimization (NPSO)’ has been proposed. In the proposed method Newton’s second law of motion has been used to …update the learning mechanism of PSO. In NPSO, particle not only learn from the position but also from the mass and acceleration of neighboring particles. The proposed method is mathematically validated at equilibrium using eigen values. Further, the proposed method has been applied on high dimensional microarray gene expression dataset. The NPSO is also compared with other state of art feature selection methods. Selected features, classification accuracy and dimension reduction are used to appraise the goodness of the proposed method. Mathematical validation and experimental results clearly validates the merits of the proposed method in field of feature selection. This paper show the classwise analysis of SRBCT, Brain1, 11-Tumor and 14-Tumor datasets. When number of classes increased dimension reduction is increased but classification accuracy of dataset is decreased. Show more

Keywords: Particle swarm optimization, law of motion, big data, microarray gene expression, cancer data, feature selection, classification accuracy

DOI: 10.3233/JIFS-181177

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Liu, Yan-Xiao | Yang, Ching-Nung | Sun, Qin-Dong | Chen, Yi-Cheng

Article Type: Research Article

Abstract: Traditional (k , n ) secret image sharing provides all-or-nothing decoding model and (k , n ) scalable secret image sharing provides progress decoding model during image reconstruction. Both these two decoding models are significance in various applications. However, the security level for real applications would change due to the dynamical environment, only one single decoding model cannot satisfy the changeable security requirement. In this work, we construct scalable secret image sharing schemes that provides both all-or-nothing and progress decoding models to satisfy the dynamical secure requirement. Each participant in our schemes only needs to keep one initial-shadow. During image …reconstruction, the dealer selects the decoding model according to current security requirement, if progress model is chosen, initial shadows can achieve image reconstruction in progress model without any modification; else if all-or-nothing model is chosen, the dealer does not need to resent new shadows to participants, the initial-shadows can be updated to satisfy all-or-nothing model efficiently. Show more

Keywords: Secret image sharing, scalable, decoding model, all-or-nothing, progress

DOI: 10.3233/JIFS-179396

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Sun, Yang | Li, Jianrong | Fu, Xueliang | Wang, Haifang | Li, Honghui

Article Type: Research Article

Abstract: Task scheduling in the cloud environment is a hot issue in current research. Aiming at the task scheduling problem in cloud environment, this paper analyses the scheduling model of cloud tasks, proposed an improved genetic algorithm (PGA) based on phagocytosis, changed the crossover operation of standard genetic algorithm (GA), formed a sub-chromosome individual after phagocytosis of two mother chromosomes, another individual was generated randomly, and the new individual generated after phagocytosis is determined by the fitness function and the load-balancing standard deviation, so that the evolution process can ensure a high proportion of high-quality individuals in the population. Ensure the …diversity of the population. Then a multi-population hybrid coevolutionary genetic algorithm (MPHC_GA) is adopted, which uses the Min-Min algorithm to generate initial multiple sub-populations, and these sub-populations are evolved by standard genetic algorithm (GA) and improved genetic algorithm (PGA) based on phagocytosis. The simulation results show that the proposed algorithm is effective in cloud task scheduling. Show more

Keywords: Task scheduling, genetic algorithm, phagocytosis, multi-population hybrid coevolutionary

DOI: 10.3233/JIFS-179398

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Chen, Limin | Li, Zhuohang | Lv, Muzhan | Xiong, Mingliang

Article Type: Research Article

Abstract: In order to improve the ability of automatic estimation and prediction of economic trend index, an intelligent prediction model of economic trend index based on rough set support vector machine is proposed. The statistical analysis of intelligent prediction of economic trend index is carried out by using the equivalent approximate linear model, and the regression analysis model of intelligent prediction of economic trend index is established. Combining with the rough set support vector machine big data fusion technology, the feature extraction and information mining are carried out in the process of intelligent prediction of economic trend index, and the statistical …time analysis series of economic trend index is constructed. The spatial distribution of economic trend index distribution series is reconstructed, and the economic trend is evaluated and predicted in the high dimensional economic trend index forecast series distribution space. The principal component characteristic analysis and fuzzy closeness analysis of economic trend index are carried out by using fuzzy relational degree scheduling method. Taking economic cost, economic development prospect and economic growth rate as constraint indexes, the method of multi-factor joint estimation is adopted. Realize economic trend index intelligent forecast. The simulation results show that the accuracy of fast estimation of economic trend index is high, the time cost is small, and the ability of intelligent prediction is stronger. Show more

Keywords: Rough set, support vector machine, economic trend index, intelligent prediction

DOI: 10.3233/JIFS-179389

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Li, Dakai | Zhang, Fan | Tian, Yuanli

Article Type: Research Article

Abstract: In the era of the Internet of Things, the way of information dissemination and the speed of information computing have changed dramatically. New generation technologies such as big data, IOTs, cloud computing, and mobile internet have rapidly developed, and the information resources in the process of using customers have promoted to value creation activities. The guiding force, therefore, the service model must also follow the changes. This paper is based on the enterprise management integration mechanism and information platform research of the Internet of Things environment, and analyses its conceptual model, the relationship between the platform and related subjects, the …value creation mechanism, the core business functions and the profit model, which have certain guiding significance for practice. The enterprise management integration mechanism and information platform research in the Internet of Things environment requires the parties to interact, share, and cooperate with each other to achieve common value creation. In addition, enterprises effectively research internal resource integration and information sharing, rationally streamline enterprise management institutions, thereby improving the quality and efficiency of business operations, giving full play to the role of internal control and risk management, so that enterprises can develop steadily. Keywords: Show more

DOI: 10.3233/JIFS-179391

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Zeng, Zhijun | Gao, Yong | Liu, Liyan | Yan, Xiaojun | Xu, Guoliang | Liu, Hongning | Ji, Yanhua

Article Type: Research Article

Abstract: Although it is very important to pay attention to the personalized medicine of tumour patients, there is quite lacking some methods to evaluate the synergistic effects of the top anti-cancer drugs in clinic. In the study, therefore, we used the network of pharmacogenetic and bioinformatics to discuss the complex interactions in the top anti-cancer drugs with the help of computer high performance operating power and network visualization. We got a total of 81 known targets from the top 10 anti-cancer drugs. The shared most targets were from the 5-fluorouracil, capecitabine and tegafur, occupying 4, 4 and 3 targets, respectively. Based …on complex network visual effect of the computer, gene set enrichment analysis displayed that the targets were mainly on five major categories. All the data showed that the two groups of drugs having some synergistic effects (5-fluorouracil, capecitabine, tegafur and tamoxifen, letrozole, respectively), which is suggests the top anti-cancer drugs’ synergic existing in combination drugs on clinic. Show more

Keywords: Computer, visualization, pharmacogenetics, caner, anti-cancer drugs

DOI: 10.3233/JIFS-179402

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-5, 2019

Authors: Song, Depeng | Li, Binbing | Qu, Yi | Chen, Yijun

Article Type: Research Article

Abstract: The frequency modulated continuous wave circular synthetic aperture radar (FMCW CSAR) is a high resolution imaging radar, which plays an important role in target recognition. However, the traditional wave number domain imaging algorithm has a low resolution for the target far from the scene center, which limits its wide applications in CSAR imaging. In this paper, when the targets are sparse or compressible, a circular convolution algorithm based on compressed sensing is proposed to improve the resolution. In the algorithm, the circular convolution and the Fourier transform is used to reduce computation cost. What’s more, the compressed sensing is applied …to improve the imaging resolution for the target far from the scene center, which can effectively avoid the complex calculation of the system kernel function in the traditional wave number domain algorithm. Some simulation results illustrate the effectiveness of the proposed method. Show more

Keywords: FMCW CSAR, compressed sensing, circular convolution, imaging

DOI: 10.3233/JIFS-179393

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Lu, Yujun | Hu, Xiaoyong | Su, Yu

Article Type: Research Article

Abstract: According to the large amount of and diversity of current industrial manufacturing data, on the basis of analyzed limitations of current industrial networking sensing system, a framework of industrial networking sensing system based on edge computing and artificial intelligence is put forward, including data-getting sensors group, first-level sensor routers, second-level sensor routers and backend severs. The above framework mainly is studied from three perspectives: structure level, workflow and key technologies, and the technology of artificial intelligence is the key to achieve this system with analysis of involved computational intelligence technology, information fusion technology and decision technology. This framework of industrial …networking sensing system has important reference value on improving timeliness and certainty of industrial networking communications, largely reduces the entire power consumption and reduce stress of background sever. Show more

Keywords: Industrial networking, perceptual layer, edge computing, artificial intelligence

DOI: 10.3233/JIFS-179403

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Wu, Peng | Li, Wei | Yan, Ming

Article Type: Research Article

Abstract: The traditional point cloud alignment method suffers from drawbacks such as a large extensive computation, low computing speed, and poor alignment accuracy. To overcome these problems, this paper proposes a fast and highly accurate algorithm based on fast point feature histograms (FPFH) algorithm and spatial constraints. The proposed algorithm first filters, denoises the point cloud dataset, and calculates the point cloud normal to obtain the FPFH eigenvalue. Then, the vertebral space is divided into three regions according to its location, and the feature points in each region are calculated. The Euclidean distance between a feature point and the boundary of …the adjacent region, and the weight coefficient corresponding to the feature point are given according to the calculated distance. The method overcomes the defect that the query feature point has a large workload in the traditional ICP algorithm and improves the registration precision of the point cloud. The experimental results show that the proposed method effectively solves the problems of the traditional point cloud registration algorithm, can effectively reduce the mismatch rate of point cloud registration, and can improve the registration accuracy and stability without reducing the registration of the elements. Show more

Keywords: Point cloud alignment, FPFH, ICP

DOI: 10.3233/JIFS-179394

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Sun, Xiang

Article Type: Research Article

Abstract: With the continuous progress of network technology, some abnormal data are often confused in network data flow, which affects network security. In order to grasp the abnormal degree of abnormal data in networks and detect the similarity of abnormal data, an optimized genetic data mining algorithm is used to mine abnormal data in network, obtain the initial population of abnormal data mining and optimize genetic operation. On this basis, the network data type and the number of network data types are adaptively adjusted to obtain the optimal abnormal data mining results. Based on Euclidean distance, the similarity value of abnormal …data in network is calculated, and the greater the similarity value is, the greater the similarity of abnormal data is and vice versa. The experimental results show that the average standard deviation of detection error and energy consumption of the proposed method are 0.00865 and 398J, respectively. This method is a reliable and energy-saving method for similarity detection of abnormal data in network, which provides an effective basis for grasping the anomaly degree of network data. Show more

Keywords: Data mining, abnormal data in network, population, optimized genetics, similarity, detection

DOI: 10.3233/JIFS-179390

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Xu, Tian | Fan, Jizhuang | Fang, Qianqian | Zhu, Yanhe | Zhao, Jie

Article Type: Research Article

Abstract: Collision detection is the core issue in physical human–robot interactions, and many detection methods based on robot dynamic models have been proposed. However, model uncertainties, especially complicated friction, seriously affect the collision detection performance of these methods. In this paper, a nonlinear disturbance observer (NDO) originally proposed for friction estimation is applied for the first time in robot collision detection. To verify that the collision detection performance of the NDO is better than that of the classical generalized momentum observer (GMO), the detection sensitivity, robustness and external torque estimation accuracy of each method are compared and analyzed. Then, to eliminate …the effects of friction uncertainties on the collision detection results, a modified nonlinear disturbance observer (MNDO) based on neural networks is proposed to improve the collision detection performance. To verify the effectiveness of the algorithm, simulations and experiments are conducted with a 6-DOF robot and two single-joint platforms. The results indicate that the proposed algorithm is accurate and effective. Show more

Keywords: Robot collision detection, NDO, GMO, friction estimation, neural networks

DOI: 10.3233/JIFS-179392

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Bian, Qian | Zhang, Xuejun | Wang, Zhenduo | Liu, Mujun | Li, Bijiang | Wu, Dongbo | Liu, Gang

Article Type: Research Article

Abstract: Multi-phase computed tomography images are widely applied to doctors’ routine interpretation of organic lesions or before human abdominal surgery. However, because of the lack of intuitive and three-dimensional (3D) observations, human factors lead to 80% of the clinical errors. A primary malignant tumor resection system based on a virtual reality (VR) helmet and a force-feedback device combined with a 3D printing model is proposed in this paper. First, we used the thin-plate spline (TPS) deformation method to register the different phase images. In the case of a metastatic tumor, a spherical scoring filter (SSF) model was built for searching the …tumor pattern with edge detection and subtraction processing, from which the initial tumors were selected on the basis of the calculated score. For hepatocellular carcinoma cases, candidates were extracted as the areas without edges by using edge detection filters on the subtraction image between the equilibrium and arterial phase images. Finally, the false positive (FP) candidate was eliminated before obtaining the 3D shape of the liver tumor in the expansion process, thus providing an accurate volume of lesions for the surgical plan for the liver resection. The results showed that our virtual surgery system enabled the user to simulate the use of a scalpel for cutting and removing the organ labels; 3D display on a VR helmet with a deformable effect; and touching organs with a force-feedback device. Our virtual surgery tools could simulate all of the effects of the doctors’ operations and make clinical practice more efficient. Show more

Keywords: Virtual surgery system, hepatocellular carcinoma (HCC), metastatic tumor, multi-detector CT (MDCT), spherical scoring filter, force-feedback device

DOI: 10.3233/JIFS-179401

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Sun, Feng | Qu, Xiao-bing | Zhu, Ling

Article Type: Research Article

Abstract: Uni-nullnorms generalize both uninorms and nullnorms. In this paper, we investigate the migrativity property for uni-nullnorms. We characterize uni-nullnorms that are α -migrative over a fixed uni-nullnorm, where the 2-neutral elements of uni-nullnorms can be the same or different. Specifically, the (α , V 1 )-migrativity of V when e  = e 1 , a  = a 1 , or e  ≠ e 1 , a  = a 1 or e  = e 1 , a  ≠ a 1 are characterized, where V and V 1 are uni-nullnorms with 2-neutral elements {e , …1}  a and {e 1 , 1}  a 1 , respectively. Show more

Keywords: Uninorms, nullnorms, 2-uninorms, uni-nullnorms, migrativity

DOI: 10.3233/JIFS-190377

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Han, Yefan | Qu, Shaojian | Wu, Zhong | Huang, Ripeng

Article Type: Research Article

Abstract: In the process of group decision making, perturbation of input data always reduces the quality of the optimal solution or even makes it unfeasible. Hence, the value of the optimal solution is often limited. In this paper, a robust optimization method is proposed to overcome the inherent uncertainty of input data in group decision making (such as experts’ unit adjustment cost). Firstly, the minimum cost consensus model based on norm definition is established. Then, four different forms of uncertainty sets are proposed, and the corresponding robust models of four minimum consensus cost models are established. Finally, in order to evaluate …the robustness of the solutions obtained by the robust consensus model, the results with different parameters are compared. The robust consensus model is also compared with the minimum cost consensus model. A numerical example proves that the result of the minimum cost consensus model is too optimistic, and the robust consensus model is more robust. Show more

Keywords: Group decision making, consensus, uncertain set, robust optimization, marketing plan

DOI: 10.3233/JIFS-190863

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Chen, Yubing | Wen, Meilin | Wang, Fei

Article Type: Research Article

Abstract: Data envelopment analysis (DEA) has become an accepted tool for assessing efficiency in a wide range of cases since it was first proposed in 1978. However, traditional DEA models need accurate inputs and outputs, which can’t be obtained or measured in many practical cases. This paper will apply DEA into uncertain environment, and propose a new DEA model with uncertain inputs and outputs based on uncertain theory. Furthermore, the uncertainty theory is utilized to convert the new uncertain DEA model into an equivalent deterministic model for simplification. Finally, this new uncertain DEA model is applied to the evaluation of scientific …research personnel to illustrate the effectiveness. Show more

Keywords: Data envelopment analysis, uncertainty theory, uncertain variable, uncertainty distribution, efficiency

DOI: 10.3233/JIFS-190784

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Wang, Dan | Zhao, Hongwei | Li, Qingliang

Article Type: Research Article

Abstract: This paper designs a brand-new image retrieval method of mammary cancer based on convolution neural network. This method simulates VLAD layer in CNN network structure, designs a trainable universal VLAD layer-NET VLAD layer, reduces dimensions and optimizes VLAD descriptors, applies structure from motion algorithm to automatically label samples, and obtains the minimum loss function value by a new training program of weakly supervised ranking loss. Experiments show that this method has improved retrieval performance compared with similar retrieval methods and non-network structure retrieval methods.

Keywords: Convolutional neural network, VLAD, loss function, medical image retrieval

DOI: 10.3233/JIFS-179386

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Deng, Xilong | Song, Dan | Wei, Li

Article Type: Research Article

Abstract: Befriending with net friends in real life is an important choice for people who live in a fast-paced lifestyle, but results are unsatisfactory and even cause a lot of malignant events. Therefore, this paper simulates the whole process of Internet friend-making through the construction of game model and field experiment, with the aim of showing the behavior logic of people with limited rational when they try to befriend with net friends in real life. This paper aims to give more behavior guidance to related participants. Results from this research show that in the process of making friends on the Internet, …the basis for people befriending with net friends in real life is that they assume that their conditions are equal. But in off-line activities, they cannot improve their effectiveness, which then terminates their communication. Therefore, this paper suggests that Internet social users should distinguish Internet friend-making from traditional friend-making, and do not have too many unrealistic expectations of Internet friend-making. Show more

Keywords: Internet friend-making, actualization, game model, experimental study

DOI: 10.3233/JIFS-179381

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Ma, Xiaohui

Article Type: Research Article

Abstract:  Aggregated search is the task of integrating results from potentially multiple specialized search services, or verticals (images, videos, news, etc.), into the Web search results. Major search engines perform what is known as Aggregated Search. Aggregated search is relatively new and its advantages need to be evaluated. With the increasing size of the data set on the network, different results retrieved from different dimensions are sometimes entirely different for a given search problem. In this paper, a new aggregated search algorithm was proposed. Firstly, the retrieval data in the vertical domain was textualized, and Doc2Vec makes the vector representation of …the data. Then the results are aggregated and output by dimension reduction and density clustering. The experimental results show that the model achieves good accuracy in 20 given queries and significantly improves the aggregated search results. Discussion about the results also allowed us to identify some useful thoughts concerning the evaluation of AS approaches. Show more

Keywords: Aggregated search, dimension reduction, density clustering, information extraction

DOI: 10.3233/JIFS-179380

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Zhao, Dingxuan | Xu, Chunbo | Ni, Tao | Zhang, Hongyan | Qiao, Ruibo

Article Type: Research Article

Abstract: Marine hydraulic manipulator is limited by its size, weight and environment, so traditional hydraulic manipulator cannot be used for marine equipment. In this paper, large displacement pump is replaced by small displacement pump, accumulator is used as absorption pulsation replace by power source, and servo valve is replaced by solenoid valve. In order to improve the dynamic response and control accuracy of the marine hydraulic manipulator. Firstly, the bond graphs model of hydraulic manipulator supplied by oil are established and analyzed. Secondly, the dynamic response characteristics of solenoid valve under different supply voltage are analyzed. Thirdly, the piecewise P optimization …of dynamic response and the fuzzy PI optimization of position control of hydraulic manipulator are carried out. Through piecewise P and fuzzy PI algorithms, not only the dynamic response of the marine manipulator is improved, but also the control accuracy of the marine manipulator is improved. Compared with the traditional hydraulic manipulator, the marine hydraulic manipulator installed volume reduced by 49%, the opening time of solenoid valve is increased by 36%, the response speed is increased by 73%, and the control accuracy is improved by 35%. Show more

Keywords: Piecewise P and fuzzy PI algorithms, accumulator, control accuracy, dynamic response, power bond graph, marine hydraulic manipulator, small pump

DOI: 10.3233/JIFS-179382

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: XinSheng, Zhang | Teng, Gao

Article Type: Research Article

Abstract: Aspect level sentiment classification task require topical polarity classification for different description aspect. There is a polysemy in the same vocabulary, and the emotional polarity is different for different objects. Word embedding can capture semantic information but cannot adapt to the polysemy. Attention mechanism has achieved good performance in the above tasks; however, it is only able to get the degree of association between words and lack able to get details description. In this paper, the ELMOs model is used to adjust the polysemy of the word. The Transformer model is used to extract the features with the highest degree …of relevance to the target object for emotional polarity classification. Our work contribution is to overcome the polysemy interference, and use the attention mechanism to model the network relationship between words, so that the model can extract important classification features according to different target words. Experiments on laptop and restaurant datasets demonstrate that our approach achieves a new state-of-the-art performance on a few benchmarks. Show more

Keywords: Text sentiment classification, fine-grained sentiment analysis, attention mechanism

DOI: 10.3233/JIFS-179383

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Long, Yingwen | Zhu, Yanxiang

Article Type: Research Article

Abstract: The difference of feeder impedance and the nonlinear load may deteriorate reactive power sharing and worsen the power quality, which may cause the breakdown of power supply in islanded microgrids. An enhanced discrete consensus algorithm considering information transmission delay is put forward in order to optimize the convergence dynamic. The proposed algorithm defines the independent iteration number of times variable for every agent, which can be transferred to its adjacent agents together with the communication data to control the times of the iteration calculation. The optimized control strategy is adopted for three-phase distributed generators to balance the reactive power sharing. …Eventually, the simulation results show that the reactive power will be evenly shared among distributed generators in proportion to their rated capacity and the proposed algorithm achieves good dynamic performance during the transition. Show more

Keywords: Reactive power sharing, distributed generator, discrete consensus algorithm, time-delay

DOI: 10.3233/JIFS-179379

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Zang, Jingfeng | Ren, Guibin | An, Yanlin | Piao, Yan

Article Type: Research Article

Abstract: Bad weather has a negative effect on the perceptual quality and degrades the performance of computer vision system. Therefore, a rain removal method based on dual-tree complex wavelet fusion is proposed. The algorithm can be further used for video surveillance system and intelligent transportation and other fields. The method analyzes from the perspective of frequency domain, using the dual-tree complex wavelet decomposition: decomposing images into low frequency sub-images and high frequency sub-images, then developing the different fusion rules. For the low frequency sub-images, fusion rules using the principal component analysis. For the high frequency sub-images, fusion rules using the local …energy matching. In this paper, an image edge enhancement algorithm based on fast guided filter is proposed, a SIFT feature matching method based on maximum likelihood estimation sampling and consistent(MLESAC) algorithm is proposed. Experiments results show that the proposed algorithm can improve the definition of images and restore the details of the target blocked by raindrops. Show more

Keywords: Raindrops removal, dual-tree complex wavelet fusion, PCA, local energy

DOI: 10.3233/JIFS-179385

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Zeng, Jiasheng | Wang, Pei

Article Type: Research Article

Abstract: Rough set theory (for short, RST) are widely applied to artificial intelligence. Fuzzy rough sets (for short, FRSs) are the results of approximation of fuzzy sets on a fuzzy approximation space. In this paper, L -fuzzy is briefly denoted by LF . We study a topological problem of FRSs based on residuated lattices, i.e., suppose that L is a complete residuated lattice, then when may the given LF -topology be consistent with the LF -topology induced by some preorder LF -relation? In order to answer this problem, the notion of LF -approximating spaces is introduced. Moreover, determinant conditions for …LF -topological spaces to be LF -approximating spaces are given. Show more

Keywords: LF-set, LF-topology, LF-approximation space, LF-rough set, LF-approximating space, (C 1) and (C 2) axioms

DOI: 10.3233/IFS-182766

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Zeng, Jun

Article Type: Research Article

Abstract: In order to improve the security of information storage in multi-domain optical network privacy protection, hybrid encoding and encryption of privacy protection information in multi-domain optical network is carried out. A hybrid coding and secure encryption technique based on particle swarm optimization (PSO) for privacy protection information in multi-domain optical network is proposed. The coding mapping equation of privacy protection information security encryption in multi-domain optical network is constructed, and the privacy protection information of multi-domain fiber network is loaded into the coding mapping equation of security encryption of privacy protection information in multi-domain fiber network. A set of characteristic …solutions describing the entropy function of the characteristic distribution of random encryption keys are obtained, and the elliptic mapping random linear combination coding and chaotic encryption key allocation are carried out. The privacy protection method of multi-domain optical fiber network is used to encrypt and decode information with mixed coding and steganography. Under the bilinear mapping coding system, the privacy-protected information in multi-domain optical network is encrypted and encrypted, stored and transmitted confidently. The simulation results show that this encryption technique has better steganography performance and better secure transmission and storage performance for the privacy protection information mixed encoding encryption in multi-domain optical network. Show more

Keywords: Particle swarm optimization algorithm, multi-domain fiber optic network, secure encryption

DOI: 10.3233/JIFS-179388

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Wang, Zhongru | Ruan, Qiang

Article Type: Research Article

Abstract: Communication network security is an important part of the digital signal processor. In particular, the process bus replaces the traditional hard wiring, which makes the network system extend from the second to the first time, greatly increasing the network scale and network traffic; the information transmitted on the process bus is absolutely large. Most requirements require strict real-time and high reliability. Therefore, information security is a major problem that threatens the security, stability, economy, and quality operation of network systems, and needs to be paid enough attention. This paper introduces the methods of information classification and information merging to improve …the real-time information. It proposes to apply network security technologies such as information encryption technology, firewall technology, mobile agent, security management technology and virtual private network (VPN) technology to office network of the electric-power industry and analysed the specific application scenarios and effects. Show more

Keywords: Network video surveillance, embedded system, digital signal processor, network security subsystem

DOI: 10.3233/JIFS-179384

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Kemal Ozdemir, M. | Esi, Ayhan | Subramanian, Nagarajan

Article Type: Research Article

Abstract: There are several notions of convergence of fuzzy number sequences in the literature. The aim of this paper is to introduce and study a new concept of the rough fuzzy ideal convergent triple sequences defined by Orlicz function. Also, some topological properties of the resulting sequence spaces of rough fuzzy numbers were examined.

Keywords: Triple sequences, rough convergence, fuzzy numbers, Orlicz function, difference sequence, duals, integral sequence, 40F05, 40J05, 40G05

DOI: 10.3233/JIFS-182832

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Wang, Dan | Zhao, Hongwei | Li, Qingliang

Article Type: Research Article

Abstract: This paper presents a medical brain image algorithm based on multi-feature fusion. Feature extraction based on convolutional neural network was used as texture information, feature extraction based on voxel information was used as morphological feature, and then the two types of features were combined in series. Feature extraction based on convolutional neural network was used as texture information, feature extraction based on voxel information was used as morphological feature, and then the two types of features were combined in series. Then the heuristic search algorithm is used to optimize the feature selection stage. Based on the feature score table extracted …by the recursive feature elimination method of support vector machine, the correlation between features is added. Moreover, through experimental analysis, the optimal value of the parameter K was selected according to the heuristic search, and the optimal feature subset was extracted after determining the value of the parameter K. Experiments show that compared with similar algorithms, this algorithm improves the accuracy and efficiency of the classification of brain images. Show more

Keywords: Convolutional neural network, multi-feature fusion, heuristic search, medical image classification

DOI: 10.3233/IFS-179387

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Aaly Kologani, M. | Jun, Y.B. | Xin, X.L. | Roh, E.H. | Borzooei, R.A.

Article Type: Research Article

Abstract: In this paper, we introduce the notion of co-annihilator in hoops and investigate some related properties of them. Then we prove that the set of filters F ( A ) form two pseudo-complemented lattices (with ∗ and ⊤) that if A has (DNP), then the two pseudo-complemented lattices are the same. Moreover, by defining the operation → on the lattice F ( A ) , we prove that F ( A ) is a Heyting algebra and by defining of the product operation, we show …that F ( A ) is a bounded hoop. Finally, we define the C  - Ann  (A ) to be the set of all co-annihilators of A , then we have that it had made a Boolean algebra. Also, we give an extension of a filter, which leads to a useful characterization of α -filters on hoops. For instance, we obtain a series of characterizations of α -filters. In addition, we show that there are no non-trivial α -filters on hoop-chains. That implies the structure of all α -filters contains only trivial α -filters on hoops. On hoops, we prove that the set of all α -filters is a pseudo-complemented lattice. Moreover, the structure of all α -filters can form a Boolean algebra under certain conditions. Show more

Keywords: Hoop, Boolean algebra, Heyting algebra, filter, co-annihilator, pseudo-complement

DOI: 10.3233/IFS-190565

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Dong, Shi | Jain, Raj

Article Type: Research Article

Abstract: Community detection is of great importance to understand the structures and functions of networks. Overlap is a significant feature of networks and overlapping community detection has attracted an increasing attention. Although many algorithms have been presented to detect overlapping communities, detection of overlapping community is still a challenging task. It can not efficiently obtain the latest community structure that the traditional static method partition the network structure. Therefore, this paper presents a new overlapping community detection algorithm based on improved KNN, the algorithm can timely adjust community structure based on different networks change, and ultimately obtains the results of the …community partition with high degree of Q module. Show more

Keywords: Social networks, overlapping community, community detection, Q module

DOI: 10.3233/JIFS-190724

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Li, Yonghong | Li, Jiang | Duan, Huiming | Qiu, Dong

Article Type: Research Article

Abstract: The purpose of this paper is to study matroids on intuitionistic fuzzy sets, so as to generalize G  - V fuzzy matroids.The ranking, union and intersection between two intuitionistic fuzzy sets are firstly defined by using the similarity function h and the accuracy function H of the intuitionistic fuzzy value. Then a G  - V intuitionistic fuzzy matroid which can be regarded as an extension of G  - V fuzzy matroids is proposed. Particularly, the induced matroid sequence and the rank function of a G  - V intuitionistic fuzzy matroid and their properties are studied.

Keywords: Fuzzy set, intuitionistic fuzzy set, matroid, fuzzy matroid, G - V intuitionistic fuzzy matroid, rank function

DOI: 10.3233/JIFS-182798

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019