Journal of Intelligent & Fuzzy Systems - Volume 35, issue 6

Authors: Mao, Wei-Lung | Suprapto,

Article Type: Research Article

Abstract: Nonlinear time series analysis and forecasting are an essential part in a diverse range of physical and natural applications. This paper presents a time-division cerebellar model articulation controller (TDCMAC) network using a modified biogeography-based optimization (modified BBO) learning algorithm for nonlinear time series and measurement data prediction. The TDCMAC method is a time windowing strategy constructed using the CMAC network. BBO algorithm is designed related to the geographical distribution of species over time and space. This study presents two modified migration functions of the essential BBO, i.e. quadratic migration BBO (QBBO) and sinusoidal migration BBO (SBBO) methods, to improve …convergence rate and quality of solution. Five nonlinear time series, including Mackey-glass, Lorenz, Rossler, Limber Pine, and Ponderosa Pine data series, are employed to investigate the proposed predictor. The TDCMAC networks using QBBO and SBBO learning algorithms are compared with the gradient descent (GD) method and other existing heuristic learning methods, including particle swarm optimization (PSO), genetic algorithm (GA), and conventional BBO methods, to verify the estimation performance of the proposed method. The performances are evaluated through an extensive simulation by computing the root mean square error (RMSE), mean absolute percentage error (MAPE), and average relative variance (ARV) metrics. Experimental results demonstrate that the proposed predictor indeed achieve more accurate performances and faster learning speed for time series prediction applications. Show more

Keywords: Time-division cerebellar model articulation controller (TDCMAC), Modified biogeography-based optimization, Nonlinear time series prediction, Mackey Glass time series, Lorenz time series, Rossler time series

DOI: 10.3233/JIFS-171120

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6199-6215, 2018

Authors: Yin, Shi | Li, Baizhou | Dong, Hengmin

Article Type: Research Article

Abstract: In recent decades, many multi-attribute decision-making methods have not been effectively applied to solve practical problems because of various shortcomings. The purpose of this paper is to develop a novel dynamic multi-attribute decision-making (DMADM) method based on the improved weights function and score function. In this paper, a novel method based on the improved entropy of interval-valued intuitionistic fuzzy sets is applied to calculate attribute weight. A time weight method is developed via the multi-target nonlinear programming model based on the ideal solution and information entropy. The influence of decision-makers’ subjective preference and objective attribute information are integrated into …the time weight. A novel ranking method based on the improved score function is used to select the best alternative in the DMADM process. Moreover, the interaction among attributes is considered by the interval-valued intuitionistic fuzzy geometric weighted Heronian means operator in the proposed method. Finally, an example of partner selection with collaborative innovation is given to verify the developed approach. This study contributes to the development of DMADM theory by using improved attribute weight, time weight, and score functions, and offers us a very useful way to deal with DMADM problems in real life. Show more

Keywords: Multi-attribute decision-making (MADM), attribute weight, time weight, score function, collaborative innovation

DOI: 10.3233/JIFS-171505

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6217-6227, 2018

Authors: Wen, Ta-Chun | Chang, Kuei-Hu | Lai, Hsin-Hung

Article Type: Research Article

Abstract: Personnel selection issues can be viewed as a complicated multicriteria decision-making (MCDM) problem. Choosing the most appropriate personnel directly influences an organization’s competitiveness and its sustainable development. Thus, the personnel selection problem is a critical issue for an organization’s success. However, such dilemmas involve quantitative and qualitative factors. Moreover, deciding on how to allocate limited resources toward cultivating talent increases the difficulty of personnel selection problems. This issue can not be solved effectively by arithmetic average-based methods. To address these issues, this paper combines the minimal variance order weighted averaging (OWA) operator and importance-performance analysis (IPA) to improve personnel selection. …The advantages of the proposed method can deal with quantity and qualitative factors simultaneously in the process of personnel selection, consider the ordered weights between assessment attributes, and establish an IPA grid to provide the reference for decision-making by the management. Finally, an empirical case study of selection of higher-education students is applied to illustrate our method. Compared with the arithmetic average and interval 2-tuple linguistic VIKOR methods, our results indicated that the proposed method generates a more accurate and reasonable ranking of personnel. Show more

Keywords: Decision analysis, human resource management, 2-tuple linguistic representation model, minimal variance OWA, importance performance analysis

DOI: 10.3233/JIFS-171686

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6229-6239, 2018

Authors: Su, Tai-Sheng | Wu, Chin-Chun | Yang, Huei-Ru

Article Type: Research Article

Abstract: The aims of this paper are to consider cost and energy consumption to solve overhead crane systems’ setting issues. The main issue is that cranes use higher frequency handling equipment in heavy industry. In the overhead crane system setting issues, the determining factors, such as cost, load and energy consumption, are fuzzy. Moreover, decision makers must simultaneously consider real-world conflicting multi-objectives. In summary the question involves a fuzzy multi-objectives problem. Therefore, this paper adopted fuzzy multi-objective programming to construct a mathematical model aimed at minimizing cost and energy consumption with reference to the crane load, recovery period and budget, to …carry out a crane system configuration. The model is used for a real problem to verify its correctness. Finally, this study provides a reference for decision makers to purchase crane device configurations. Show more

Keywords: Fuzzy multi-objective linear programming, overhead crane systems, energy consumption and cost, equipment assignment

DOI: 10.3233/JIFS-171763

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6241-6253, 2018

Authors: Moradi, Mojtaba | Hafezalkotob, Ashkan | Ghezavati, Vahidreza

Article Type: Research Article

Abstract: Sustainability is one of the most significant problems in today’s world and the concept of sustainable development is being an important objective in construction projects. Since the large projects have enormous and different activities that should be scheduled by considering resource constraint and precedence relationship between them, the resource-constrained project scheduling problem (RCPSP) is a NP-hard problem. In this study, fuzzy project scheduling model is presented to solve RCPSP under uncertainty in availability of the resources and activities duration simultaneously. Subcontractors have incentive to share their resources in the form of coalition in order to reduce activities time and cost. …In this research, cooperative game methods are introduced for fair allocating utility of the project, as well as, present supper-additivity, stability and satisfaction level of each coalition. Finally, sustainability concept is analyzed in RCPSP and cooperation of subcontractors in a coalition form, whereas in the previous researches these topics addressed separately or generally in project scheduling to minimize the makespan and maximize the profit of project. The results of the proposed model indicate that the subcontractors can obtain more profit and the balance between sustainability indicators in project management arises by collaboration. Show more

Keywords: Sustainability, fuzzy project scheduling, RCPSP, cooperative game theory, satisfaction level

DOI: 10.3233/JIFS-171821

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6255-6267, 2018

Authors: Senthilkumar, R. | Justin Sunil Dhas, G.

Article Type: Research Article

Abstract: Fractional order proportional, Integral and a derivative controller is a special kind of controller which is used to regulate the output voltage of a class of sepic converter to the desired level. Tuning of fractional Proportional, Integral and Derivative controller (FOPID) is achieved by different metaheuristic algorithm and the optimization performance target is chosen as minimizing the integral square error (ISE). This paper presents a performance analysis of Single Ended Primary Inductance Converter (SEPIC) by time response specifications such as rise time, settling time and steady-state error and further, the results are compared with the controllers designed by Genetic Algorithm …(GA), Particle Swarm Optimization (PSO) and Queen Bee based Genetic Algorithm (QBGA). The design and implementation of fractional order controller for a closed loop control of converter is done by utilizing a MATLAB/SIMULINK environment. Results show that QBGA algorithm exhibit better performance as compared to other optimization technique for voltage mode controller in terms of disturbance rejection. Show more

Keywords: SEPIC converter, fractional PID controller, GA, PSO, QBGA

DOI: 10.3233/JIFS-171892

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6269-6276, 2018

Authors: Owolabi, Taoreed O. | Gondal, Mohammed A.

Article Type: Research Article

Abstract: Laser induced breakdown spectroscopy (LIBS) is an excellent technique for analysis of solid and liquid samples. However there are inherent problems with concentration determination of elements present in the test sample with better accuracy. In order to address this challenge, hybrid fusion of extreme learning machine (ELM) and support vector regression (SVR) is proposed for the first time. Extreme learning machine (ELM) is a non-linear chemo-metric method which has inherent capacity to approximate any non-linear relation describing the laser induced plasma. However, ELM surfers from over-fitting which affects its accuracy for spectroscopic regression. On the other hand, SVR is a …non-linear chemo-metric tool based on statistical learning theory and overcomes the problem of over-fitting by proper tuning of its hyper-parameters. The merits of both chemo-metrics are harnessed in this work and implemented for quantitative analysis of LIBS spectra of seven standard bronze samples. The performance of ELM-SVR model which uses the output of ELM as its input is compared to that of SVR-ELM model which takes the output of SVR as its input. The hyper-parameters of the proposed models are optimized using gravitational search algorithm (GSA). On the bases of root mean square error (RMSE) as a measure of model performance, ELM-SVR performs better than SVR, ELM and SVR-ELM model with performance improvement of 95.76%, 89.33% and 52.71%, respectively. The accuracy of the proposed hybrid models would be of immense significance for quick quantitative analysis in LIBS and eventually promotes wide applicability of the technique. Show more

Keywords: LIBS spectra, extreme learning machine, gravitational search algorithm, support vector regression, quantitative analysis, hybrid model

DOI: 10.3233/JIFS-171979

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6277-6286, 2018

Authors: Heidari, S.V. | Soleymani, S. | Faghihi, F. | Mozaffari, B.

Article Type: Research Article

Abstract: The current study presents a new method for allocation of the contribution of voltage harmonic distortion for consumers and utilities. This method utilizes three-phase voltage and current waveforms at the point of common coupling (PCC) by applying an adaptive Kalman filter to estimate the amplitude and phase angle of the waveform. The fuzzy adaptation part of the Kalman filter allows resetting of the Kalman gain for fast tracking of system variations under transient conditions. Singular value decomposition based on recessive least square is used to estimate the Norton equivalent circuit for the entire system. In the proposed method an Indicator …of the voltage value is used to determine the contribution of harmonic distortion for both sides. The characteristics of the proposed method were investigated through simulation of a nonlinear load which is connected to the distribution system and practical data from 130 kV distribution system in north-west of Iran. Show more

Keywords: Harmonic component contributions, fuzzy system, kalman filter, distribution system

DOI: 10.3233/JIFS-172055

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6287-6299, 2018

Authors: Konwar, Nabanita | Davvaz, Bijan | Debnath, Pradip

Article Type: Research Article

Abstract: In this paper we study approximation properties (APs) and bounded approximation properties (BAPs) in the setting of intuitionistic fuzzy n -Banach spaces (IFnBSs). Further, we define strong intuitionistic fuzzy n -continuous and strong intuitionistic fuzzy n -bounded operators and using them we prove the existence of an IFnBS with AP. In addition, we provide examples which show that there exist IFnBSs with the AP which fail to have the BAP.

Keywords: Intuitionistic fuzzy n-Banach space; approximation property, bounded approximation property.

DOI: 10.3233/JIFS-181094

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6301-6312, 2018

Authors: Izhar, Muhammad | Khan, Asghar | Mahmood, Tariq

Article Type: Research Article

Abstract: The main motivation behind this paper is to study some structural properties of a non-associative structure Abel Grassmann’s groupoid (AG-groupoid) in terms of double-framed soft sets (DFS sets) as it hasn’t attracted much attention compared to associative structures. An AG-groupoid can be referred to as a non-associative semigroup, as the main difference between a semigroup and an AG-groupoid is the switching of an associative law. In this paper, we introduce the concept of (M , N )-double-framed soft ideals (briefly, (M , N )-DFS ideal) of AG-groupoids and investigate some properties of these notions. We have shown that every (M …, N )-DFS ideal is (M , N )-DFS AG-groupoid but the converse is not true. This is shown with the help of an example. We also discuss the properties of (M , N )-DFS ideals in regular AG-groupoids. Moreover a decision making algorithm based on DFS-sets is given. Show more

Keywords: DFS set, (M , N)-DFS AG-groupoids, (M , N)-DFS ideal, regular AG-groupoid, choice values, DFS-weighted set

DOI: 10.3233/JIFS-181119

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6313-6327, 2018