Journal of Intelligent & Fuzzy Systems - Volume 40, issue 5

Authors: Luo, Sheng

Article Type: Research Article

Abstract: An information system as a database that represents relationships between objects and attributes is an important mathematical model in the field of artificial intelligence. Hybrid data means boolean, categorical, real-valued, set-valued data and missing data in this paper. A hybrid information system is an information system where its attribute is hybrid data. This paper proposes a three-way decision method based on hybrid data. First, the distance between two objects based on the conditional attribute set in a given hybrid information system is developed and Gaussian kernel based on this distance is acquired. Then, the fuzzy T cos -equivalence relation, …induced by this information system, is obtained by using Gaussian kernel. Next, the decision-theoretic rough set model in this hybrid information system is presented. Moreover, a three-way decision method is given by means of this decision-theoretic rough set model and inclusion degree between two fuzzy sets. Finally, an example is employed to illustrate the feasibility of the proposed method, which may provide an effective method for hybrid data analysis in real applications. Show more

Keywords: Three-way decision, hybrid data, decision-theoretic rough set, gaussian kernel, feasibility

DOI: 10.3233/JIFS-182764

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8639-8650, 2021

Authors: Shobha Rani, N. | Yadhu, C. R. | Karthik, U.

Article Type: Research Article

Abstract: Assessing the age of an individual via bones serves as a technique in determination of individual skills. In this work, the assessment of chronological age for varying age groups of individuals is carried out using left hand wrist radiographs. The datasets employed for experimentation are preprocessed and extracted using an automated segmentation technique using bit plane level data of radiograph images. The flow of proposed work is comprised of three stages, in stage 1 preprocessing is carried out, classification of preprocessed radiographs are classified into male and female samples using convolution kernels based deep neural net. Further, distance features are …extracted from the origin of carpal bones to tip of extracted phalangeal regions in the classified outcomes from stage 2 using imtool image analyzer. Finally, classification of distance features is performed using Support Vector Machines with Gaussian Kernel (SVM-GK) to label the radiographs into ages from 1 to 17. The experimentation is performed on the datasets of Pediatric Bone Age challenge of Radiological Society of North America (RSNA) of about 12000 images of 1–17 year age groups. The convergence between actual and clinically validated chronological age is also tested with Gaussian process regression model (GPRM) along with SVM. A very minimal loss of about 4.7% is occurred during classification using deep neural network. The classification accuracy is found to be 76.8% and 88.1% and 0.75 and 1.41 RMSE with respect to GPRM and SVM-GK. Show more

Keywords: Bone age assessment, deep neural net, GPRM, SVM-GK, medical image processing, classification

DOI: 10.3233/JIFS-190779

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8651-8663, 2021

Authors: Fezai, Radhia | Mansouri, Majdi | Abodayeh, Kamaleldin | Nounou, Hazem | Nounou, Mohamed | Puig, Vicenç | Bouzrara, Kais

Article Type: Research Article

Abstract: This paper aims at improving the operation of the water distribution networks (WDN) by developing a leak monitoring framework. To do that, an online statistical hypothesis test based on leak detection is proposed. The developed technique, the so-called exponentially weighted online reduced kernel generalized likelihood ratio test (EW-ORKGLRT), is addressed so that the modeling phase is performed using the reduced kernel principal component analysis (KPCA) model, which is capable of dealing with the higher computational cost. Then the computed model is fed to EW-ORKGLRT chart for leak detection purposes. The proposed approach extends the ORKGLRT method to the one that …uses exponential weights for the residuals in the moving window. It might be able to further enhance leak detection performance by detecting small and moderate leaks. The developed method’s main advantages are first dealing with the higher required computational time for detecting leaks and then updating the KPCA model according to the dynamic change of the process. The developed method’s performance is evaluated and compared to the conventional techniques using simulated WDN data. The selected performance criteria are the excellent detection rate, false alarm rate, and CPU time. Show more

Keywords: Leak detection, water distribution networks, kernel principal component analysis, online reduced kernel generalized likelihood ratio test, exponentially weighted moving average

DOI: 10.3233/JIFS-191524

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8665-8681, 2021

Authors: Arivudainambi, D. | Pavithra, R.

Article Type: Research Article

Abstract: Wireless Sensor Network (WSN) has emerged recently due to its advancements and applications in various scientific and industrial fields. WSN consists a set of low cost and readily deployable sensors to monitor targets and recognise the physical phenomena. The principal challenge in WSN is to deploy these sensor nodes in optimal positions to achieve efficient network. Such network should satisfy the quality of service requirements in order to achieve high performance levels. Hence, this paper focuses on target Q-coverage problem where each target requires different number of sensors to monitor them. A Sequential Vertex Coloring based Sensor Placement (SVC-SP) algorithm …is proposed to determine the number of sensors required and its optimal spot to satisfy the coverage quality requirement. The SVC-SP algorithm determines sensor requirement by partitioning the target set into independent subsets depending on the target’s position and the sensor’s sensing range. Each independent set consists set of targets that are nearer in the network such that a common sensor is sufficient to monitor them. The cardinality of such independent subsets provides the sensor requirement for target coverage. The optimal spot for each target is determined by the mean positioning of the targets in each independent set. This process is repeated until the q-requirement for each target is satisfied. Further, to improve the optimal spot for sensors, the random based SVC-SP algorithm, cuckoo search based SVC-SP algorithm and the genetic algorithm based SVC-SP algorithm are utilized. The simulation results show that genetic algorithm based SVC-SP algorithm performs better than other existing algorithms. Show more

Keywords: Optimal sensor placement, target coverage, Q-coverage, vertex coloring, sequential vertex coloring

DOI: 10.3233/JIFS-191795

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8683-8695, 2021

Authors: Miao, Ya Lin | Cheng, Wen Fang | Ji, Yi Chun | Zhang, Shun | Kong, Yan Long

Article Type: Research Article

Abstract: Aiming at the problem that the Aspect-based sentiment analysis in Chinese has low recognition rate due to many steps, this paper proposes an improved BiLSTM-CRF model based on combine the Chinese character vector and Chinese words position feature, which can extract attribute words and sentiment words jointly simultaneously, while extracting Polarity judges of sentiment words. Experiments show that the improved model improves the precision rate by 9.2%  13.32%, recall rate improves 0.48%  21.29%, F-measure improves 7.33%  15.74% compared with Conditional Random Fields (CRF) model and Long Short Term Memory (LSTM) model on the self-built 6357 mobile reviews dataset. The experimental …results show that the model improves the accuracy of Aspect-based sentiment analysis and can effectively obtain the information required by users need in evaluation texts. Show more

Keywords: Aspect-based sentiment analysis in Chinese, BiLSTM-CRF model, attribute words, emotional words, mobile reviews

DOI: 10.3233/JIFS-192078

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8697-8707, 2021

Authors: Barma, Partha Sarathi | Dutta, Joydeep | Mukherjee, Anupam | Kar, Samarjit

Article Type: Research Article

Abstract: This study designs a new variant of the capacitated vehicle routing problem (CVRP) under a fuzzy environment. In CVRP, several vehicles start their journey from a central depot to provide services to different cities and finally return to the depot. This paper introduces an additional time beyond the service time at each city to fulfill the pre-ordered demands. The need for this excess service time is to provide the services to new customers who are not enlisted at the start of the process. It is a market enhancement step. The proposed model’s main objective is to find the maximum time-dependent …profit by using the optimum number of vehicles in an appropriate route and spending optimum excess service time in each city. The model considers travel time and travel cost as fuzzy numbers. An expected value model (EVM) is formulated using the credibility approach on fuzzy variables. A hybrid meta-heuristic method combining a genetic algorithm (GA) and bacteria foraging optimization algorithm (BFOA) is designed to solve the proposed model. The proposed model is explained with the help of some numerical examples. Sensitivity analyses based on different independent parameters of the algorithms are also conducted. Show more

Keywords: Capacitated vehicle routing problem, profit maximization, fuzzy credibility theory, hybrid algorithm, genetic algorithm, bacteria foraging optimization algorithm

DOI: 10.3233/JIFS-192134

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8709-8725, 2021

Authors: Singh, Rajvir | Rama Krishna, C. | Sharma, Rajnish | Vig, Renu

Article Type: Research Article

Abstract: Dynamic and frequent re-clustering of nodes along with data aggregation is used to achieve energy-efficient operation in wireless sensor networks. But dynamic cluster formation supports data aggregation only when clusters can be formed using any set of nodes that lie in close proximity to each other. Frequent re-clustering makes network management difficult and adversely affects the use of energy efficient TDMA-based scheduling for data collection within the clusters. To circumvent these issues, a centralized Fixed-Cluster Architecture (FCA) has been proposed in this paper. The proposed scheme leads to a simplified network implementation for smart spaces where it makes more sense …to aggregate data that belongs to a cluster of sensors located within the confines of a designated area. A comparative study is done with dynamic clusters formed with a distributive Low Energy Adaptive Clustering Hierarchy (LEACH) and a centralized Harmonic Search Algorithm (HSA). Using uniform cluster size for FCA, the results show that it utilizes the available energy efficiently by providing stability period values that are 56% and 41% more as compared to LEACH and HSA respectively. Show more

Keywords: Wireless sensor network, clustered architecture

DOI: 10.3233/JIFS-192177

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8727-8740, 2021

Authors: Li, Dong | Liu, Shulin | Gao, Furong | Sun, Xin

Article Type: Research Article

Abstract: Classification methods play an important role in many fields. However, they cannot effectively classify the samples from sample spaces that are varying with time, for they lack continual learning ability. A continual learning classification method for time-varying data space based on artificial immune system, CLCMTVD, is proposed. It is inspired by the intelligent mechanism that memory cells of the biological immune system can recognize and eliminate previous invaders when they attack again very fast and more efficiently, and these memory cells can evolve with the evolution of previous invaders. Memory cells were continuously updated by learning testing data during the …testing stage, thus realize the self-improvement of classification performance. CLCMTVD changes a linearly inseparable spatial problem into many classification problems of several different times, and it degenerates into a common supervised learning classification method when all data independent of time. To assess the performance and possible advantages of CLCMTVD, the experiments on well-known datasets from UCI repository, synthetic data and XJTU-SY rolling element bearing accelerated life test datasets were performed. Results show that CLCMTVD has better classification performance for time-invariant data, and outperforms the other methods for time-varying data space. Show more

Keywords: Artificial immune system, classification, continual learning, machine learning, time-varying data

DOI: 10.3233/JIFS-200044

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8741-8754, 2021

Authors: Oguz, Gulay | Davvaz, Bijan

Article Type: Research Article

Abstract: Molodtsov proposed the theory of soft sets which can be considered as a recent mathematical tool to deal with uncertainties. The main purpose of this paper is to give the definition of soft topological hypergrupoid by examining the concept of hypergrupoid which is one of the hyperystructures with soft set theory from the topological point of view. Also, the relation between soft topological hypergroupoids and soft hypergroupoids is examined and some theoretical results are obtained. By introducing the concept of soft good topological homomorphism, the category of soft topological hypergrupoids is constructed. At last, the definition of soft topological subhypergrupoid …is presented and some related properties are studied. Show more

Keywords: Soft set, topological hypergroupoid, soft hypergrupoid, soft topological hypergroupoid

DOI: 10.3233/JIFS-200242

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8755-8764, 2021

Authors: Zhao, Hu | Sayed, O.R. | El-Sanousy, E. | Ragheb Sayed, Y.H. | Chen, Gui-Xiu

Article Type: Research Article

Abstract: Different from the separation axioms in the framework of (L , M )-fuzzy convex spaces defined by Liang et al.(2019). In this paper, we give some new investigations on separation axioms in (L , M )-fuzzy convex structures by L -fuzzy hull operators and r -L -fuzzy biconvex. We introduce the concepts of r -LFS i spaces where i  = {0, 1, 2, 3, 4}, and obtain various properties. In particular, we discuss the invariance of these separation properties under subspace and product.

Keywords: r-LFS0 space, r-LFS1 space, r-LFS2 space, r-LFS3 space, r-LFS4 space

DOI: 10.3233/JIFS-200340

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 8765-8773, 2021