Journal of Intelligent & Fuzzy Systems - Volume 39, issue 5

Authors: Vijayabalaji, Srinivasan | Balaji, Parthasarathy

Article Type: Research Article

Abstract: In 1982, Pawlak set up a fresh approach to deal with uncertainties namely rough set theory, Multiple-Criteria Decision Making (MCDM) first traced by Benjamin Franklin in 17th century. Several researchers did significant contribution to MCDM thereafter. An assignment problem involves what happens to the effective function when each of a number of sources is associated with the same number of destinations. Using MCDM, Rough matrices and Assignment model we are inducing an idea to pick Best’11 in all three formats (Test, One Day Internationals (ODI), Twenty20 International matches (T20I)) in the game of cricket with players from two nationals. Using …the existing data, we are providing best batting position for any player to maximize team’s run. In addition, based on the preprocessing of informations, we are bringing some new indices to pick Indian squad for the 2019 World Cup cricket held in England from May 2019 to July 2019. After making a selection from our framework, we will compare the list of selected players by Board of Cricket Control Board in India (BCCI) and giveaway the percentage of similarity between the our selection against BCCI’s selection. We pick 11 players after selecting 15 players from 24 players to formulate the assignment model and offer the best batting order to optimize team’s run. Show more

Keywords: Rough set, rough matrix, information systems, MCDM, best’11, assignment problem

DOI: 10.3233/JIFS-200784

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7431-7447, 2020

Authors: George Fernandez, I. | Arokia Renjith, J.

Article Type: Research Article

Abstract: Cloud computing technology is playing a major role in the industry and real-life, for providing fast services such as data sharing and allocating the cloud resources that are paid and truly required. In this scenario, the cloud users are scheduled according to the rule-based systems for attempting to automate the matching between computing requirements and resources. Even though, the majority auto-scaling algorithms only helped as indicators for simple resource utilization and also not considered both cloud user needs and budget concerns. For this purpose, we propose a new model which is the combination of auto-scaling algorithms, resource allocation and scheduling …for allocating the appropriate resources and scheduled them. This model consists of three new algorithms namely Grey Wolf Optimization and Fuzzy rules based Resource allocation and Scheduling Algorithm (GWOFRSA), Auto-Scaling Algorithm for Cloud based Web Application (ASACWA) and Auto-Scaling Algorithm for handling Distributed Computing Tasks (ASADCT). Here, we introduce new auto-scaling algorithms for enhancing the performance of cloud services. In this work, the optimization technique is used to predict the cloud server workload, resource requirements and it also uses fuzzy rules for monitoring the resource utilization and the size of virtual machine allocation process. According to the workload prediction, the completion time is estimated for each cloud server. The experiments are conducted by using a simulator called CloudSim environment of Java programming and compared with the existing works available in this direction in terms of resource utilization and enhance the cloud performance with better Quality of Service of Virtual Machine allocation, Missed Deadline, Demand Satisfaction, Power Utilization, CPU Load and throughput. Show more

Keywords: Grey Wolf Optimization, resource allocation, scheduling, auto-scaling, virtual machine, cloud computing and performance

DOI: 10.3233/JIFS-200787

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7449-7467, 2020

Authors: Liu, Peide | Akram, Muhammad | Sattar, Aqsa

Article Type: Research Article

Abstract: The complex q-rung orthopair fuzzy set (Cq-ROFS), an efficient generalization of complex intuitionistic fuzzy set (CIFS) and complex Pythagorean fuzzy set (CPFS), is potent tool to handle the two-dimensional information and has larger ability to translate the more uncertainty of human judgment then CPFS as it relaxes the constrains of CPFS and thus the space of allowable orthopair increases. To solve the multi-criteria decision making (MCDM) problem by considering that criteria are at the same priority level may affect the results because in realistic situations the priority level of criteria is different. In this manuscript, we propose some useful prioritized …AOs under Cq-ROF environment by considering the prioritization among attributes. We develop two prioritized AOs, namely complex q-rung orthropair fuzzy prioritized weighted averaging (C-qROFPWA) operator and complex q-rung orthropair fuzzy prioritized weighted geometric (Cq-ROFPWG) operator. We also consider their desirable properties and two special cases with their detailed proofs. Moreover, we investigate a new technique to solve the MCDM problem by initiating an algorithm along with flowchart on the bases of proposed operators. Further, we solve a practical example to reveal the importance of proposed AOs. Finally, we apply the existing operators on the same data to compare our computed result to check the superiority and validity of our proposed operators. Show more

Keywords: Complex q-rung orthopair fuzzy set, prioritized weighted averaging operator, prioritized weighted geometric operator, decision making

DOI: 10.3233/JIFS-200789

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7469-7493, 2020

Authors: Xia, Daoxun | Guo, Fang | Liu, Haojie | Yu, Sheng

Article Type: Research Article

Abstract: The recent successful methods of person re-identification (person Re-ID) involving deep learning have mostly adopted supervised learning algorithms, which require large amounts of manually labelled data to achieve good performance. However, there are two important unresolved problems, dataset annotation is an expensive and time-consuming process, and the performance of recognition model is seriously affected by visual change. In this paper, we primarily study an unsupervised method for learning visual invariant features using networks with temporal coherence for person Re-ID; this method exploits unlabelled data to learn expressions from video. In addition, we propose an unsupervised learning integration framework for pedestrian …detection and person Re-ID for practical applications in natural scenarios. In order to prove the performance of the unsupervised person re-identification algorithm based on visual invariance features, the experimental results were verified on the iLIDS-VID, PRID2011 and MARS datasets, and a better performance of 57.5% (R-1) and 73.9% (R-5) was achieved on the iLIDS-VID and MARS datasets, respectively. The efficiency of the algorithm was validated by using BING + R-CNN as the pedestrian detector, and the person Re-ID system achieved a computation speed of 0.09s per frame on the PRW dataset. Show more

Keywords: Person re-identification, unsupervised learning, pedestrian detection, object recognition, visual invariant features

DOI: 10.3233/JIFS-200793

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7495-7503, 2020

Authors: Li, Meng | Zhao, Yifei | Xiong, Xinglong | Ma, Yuzhao

Article Type: Research Article

Abstract: Synchronous delivery with different vehicles, as an emerging concept of the delivery network, improves the efficiency of the modern logistics system significantly, which gradually gives birth to a new issue: the traveling salesman problem with drone (TSP-D). In this paper, we propose a one-truck-multiple-drone (OTMD) model on the base of the TSP-D. Compared with the traditional one-truck-one-drone (OTOD) and multiple drones models, our scheme introduces a united objective function into the optimization calculation. In terms of the proposed multiple levels iterative theory, we can compute the optimal synchronous delivery network that takes both the total delivery time and the number …of drones into consideration. Four types of customer distributions are employed to investigate the OTMD model and its associated calculation approaches. Comparing the parameters of the optimal network in different delivery models, we study the relationship among the total delivery time, customer distribution and the number of serving drones. These simulation results verify the feasibility and practicality of the OTMD, and demonstrate the features of optimization calculation with different customer distributions, being beneficial to improve the efficiency of the model logistics system. Show more

Keywords: Traveling salesman problem with drone (TSP-D), one-truck-multiple-drone (OTMD) model, optimization calculation, modern logistics system

DOI: 10.3233/JIFS-200818

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7505-7519, 2020

Authors: Senthilkumar, G. | Chitra, M.P.

Article Type: Research Article

Abstract: In the recent years increase in computer and mobile user’s, data storage has become a priority in all fields. Large- and Small-Scale businesses today thrive on their data and they spent a huge amount of money to maintain this data. Cloud Storage provides on– demand availability of IT services via Large Distributed Data Centers over High Speed Networks. Network Virtualization is been considered as a recent proliferation in cloud computing which emerges as a Multifaceted method towards future internet by facilitating shared resources. Provisioning of the Virtual Network is considered to be a major challenge in terms of creating NP …hard problems, minimization of workflow processing time under control resource etc. In order to cope up with the challenges our work has proposed an Ensemble Dynamic Optimization based on Inverse Adaptive Heuristic Critic (IAHC) for overcoming the virtual network provisioning in cloud computing. Our approach gets observed from Expert Observation and provides an approximate solution when various workflows arrives online at various Window Time (WT). It also provides an Optimal Policy for predicting the effect of Resource Allocation of one task for Present as well as Future time Windows. In order to the above approaches it also avoids the high sample complexity and maintains the cost while scaling up to provide Resource Provision. Therefore, our work achieves an adequate policy towards Resource Allocation, reduces the Cost as well as Energy Consumption and deals with real time uncertainties to avoid the Virtual Network provisioning. Show more

Keywords: Inverse adaptive heuristic critic, dynamic optimization, reward feature, network virtualization, user resource allocation

DOI: 10.3233/JIFS-200823

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7521-7535, 2020

Authors: Mahmood, Asma | Abbas, Mujahid

Article Type: Research Article

Abstract: The aim of this paper is to construct a matrix of interpersonal influences employing TOPSIS and then to apply the matrix in influence model and doubly extended TOPSIS. Entries of that matrix are obtained from coefficients of relative closeness. Such a systematically constructed matrix performs better than the direct influence matrix because of the consideration of alternatives under certain criteria/attributes. Implementation of such influence matrix improves an influence model and group decision process. In this paper, TOPSIS is used for individual as well as group decisions. Once the decisions are reached by individuals with the help of TOPSIS, then coefficients …of relative closeness are obtained and matrix of interpersonal influences is constructed. This matrix is used in influence model and to construct the influenced decision matrices. These influenced decision matrices are aggregated to get the collective decision. This strategy is based on the fact that the decisions taken by individuals affect their collective decision in future. Show more

Keywords: Group decision making, social influence networks, multi criteria decision making, TOPSIS

DOI: 10.3233/JIFS-200833

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7537-7546, 2020

Authors: Jin, Chen | Xu, Zeshui | Wang, Jinwei

Article Type: Research Article

Abstract: With the rapid development of economy and industrialization, environmental problems, especially haze pollution, are being more and more serious. When assessing the economic losses caused by haze, although the traditional quantitative method can show the amount of economic losses visually, there are also some inaccuracies in the calculation process. Based on the situation, we propose a new method called uncertain probabilistic linguistic analytic hierarchy process (UPL-AHP), which combines traditional analytic hierarchy process with uncertain probabilistic linguistic term sets to process decision information in complex problems. Firstly, we propose the concept of uncertain probabilistic linguistic comparison matrix. Then, a new approach …is given to check and improve the consistency of an uncertain probabilistic linguistic comparison matrix. After that, we introduce the application of UPL-AHP in group decision making. Finally, the proposed method is used to analyze a practical case concerning the economic losses of haze. Some relevant policy recommendations are given based on the results. Show more

Keywords: Haze pollution, economic losses, probabilistic linguistic term set, comparison matrix, analytic hierarchy process, uncertainty

DOI: 10.3233/JIFS-200834

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7547-7569, 2020

Authors: Peng, Xindong | Smarandache, Florentin

Article Type: Research Article

Abstract: The rare earth industry is a crucial strategic industry that is related to the national economy and national security. In the context of economic globalization, international competition is becoming increasingly fierce, and the rare earth industry is facing a more severe survival and development environment than ever before. Although China is the greatest world’s rare earth country in rare earth reserves, production, consumption and export volume, it is not a rare earth power. The rare earth industry has no right to speak in the international market. The comparative advantage is weakening and the security of rare earth industry appears. Therefore, …studying the rare earth industry security has important theoretical and practical significance. When measuring the China’s rare earth industry security, the primary problem involves tremendous uncertainty. Neutrosophic soft set (NSS), depicted by the parameterized form of truth membership, falsity membership and indeterminacy membership, is a more serviceable pattern for capturing uncertainty. In this paper, five dimensions of rare earth industry security are identified and then prioritized against twelve different criteria relevant to structure, organization, layout, policy and ecological aspects of industry security. Then, the objective weight is computed by CRITIC (Criteria Importance Through Inter-criteria Correlation) method while the integrated weight is determined by concurrently revealing subjective weight and objective weight. Later, neutrosophic soft decision making method based CoCoSo (Combined Compromise Solution) is explored for settling the issue of low discrimination. Lastly, the feasibility and validity of the developed algorithm is verified by the issue of China’s rare earth industry security evaluation. Show more

Keywords: Rare earth industry security, neutrosophic soft set, CoCoSo, CRITIC

DOI: 10.3233/JIFS-200847

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7571-7585, 2020

Authors: Zhang, Li | Cheng, Shufeng | Liu, Peide

Article Type: Research Article

Abstract: Probability multi-valued neutrosophic sets (PMVNSs) can better describe the incomplete and indeterminate evaluation information, and the ELECTRE method can rank the alternatives in the light of the outranking relations among criteria. To combine their advantages, this paper introduces an extended ELECTRE method to address multi-criteria group decision-making (MCGDM) problems with the information of PMVNSs. Firstly, we introduce the definitions of PMVNSs and the classical ELECTRE method, discuss the ELECTRE-based outranking relations for PMVNSs and analyze some properties of them. Furthermore, the probability multi-valued neutrosophic ELECTRE method is developed to address MCGDM problems based on the proposed distance measure and outranking …relations for PMVNSs. Finally, a typical example for logistics outsourcing provider selection is devoted to demonstrate the feasibility of the proposed approach. Moreover, the same example-based comparisons with other existing methods are carried out, the results show our proposed approach outperforms the existing methods in solving the MCGDM problems with PMVNSs. Show more

Keywords: ELECTRE, outranking relations, probability multi-valued neutrosophic sets, MCGDM

DOI: 10.3233/JIFS-200861

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7587-7604, 2020