Journal of Intelligent & Fuzzy Systems - Volume 35, issue 1

Authors: Deng, Xiaoheng | Zeng, Detian | Shen, Hailan

Article Type: Research Article

Abstract: This paper presents a causation analysis model for traffic accident. Traffic accident is a result influenced by the interaction of various factors. Considering the characteristic of multi-dimensional and multi-layer in traffic accident data, a model which based on traffic accident historical data on the city of Guiyang in 2015 was built to find the main reasons and potential rules of traffic accidents. The model starts from the four main dimensions such as the drivers, the vehicles, the time-address and the environment, and uses a way which based on AHP and hybrid Apriori-Gentic algorithm to mine causes of accident. First of …all, the analytic hierarchy process (AHP) is used to sort the importance of the influencing factors about accident. On the basis of objective analysis, the influencing factors are quantified and the main influencing factors are selected. Then the genetic algorithm combined with Apriori is used to analyze the main influencing factors and find the expected association rules out. The experimental result shows that the model can improve the accuracy of mining and find more expected association rules. Finally the hybrid algorithm is parallelized to reduce time complexity, which makes the model has a good application potential. Show more

Keywords: Traffic accident, causational analysis, AHP, Apriori, genetic algorithm

DOI: 10.3233/JIFS-171250

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 767-778, 2018

Authors: Liu, Peide | Liu, Junlin | Chu, Yanchang | Zhang, Yuming

Article Type: Research Article

Abstract: As we all know, there are many methods to describe the different kinds of quantitative or qualitative information. However, it is necessary to extend them to express complex information by combining the qualitative and quantitative mode. In this paper, we firstly define the neutrosophic trapezoidal fuzzy linguistic numbers (NTFLNs) by combining the neutrosophic sets (NSs) with linguistic variables (LVs) to express complex information. In addition, the Frank operations are a generalization of some existing operations with a parameter. Therefore, we extend the Frank operations to the NTFLNs, and then we propose the neutrosophic trapezoidal fuzzy linguistic Frank weighted averaging (NTFLFWA) …operator and the neutrosophic trapezoidal fuzzy linguistic Frank weighted geometric (NTFLFWG) operator. Further, some desirable properties of them are studied such as idempotency, boundedness and monotonicity. Moreover, two methods based on the NTFLFWA and NTFLFWG operators for the multiple attribute group decision making (MAGDM) problems are developed. Finally, an empirical example on choice of the emergency logistics supplier is given to demonstrate the effectiveness of the developed methods. Show more

Keywords: Multiple attribute group decision making, interval-valued hesitant uncertain linguistic set, Bonferroni mean, geometric Bonferroni mean

DOI: 10.3233/JIFS-171278

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 779-791, 2018

Authors: Wang, Zelin | Wang, Ying-Ming | Wang, Liang

Article Type: Research Article

Abstract: The aim of this paper is to investigate the multi-attribute group decision making (MAGDM) problems with respect to psychological behavior of regret aversion of decision makers (DMs), in which the attribute values are expressed in multi-granular linguistic terms and numerical values. This study proposes a general model based on two-tuple linguistics to deal with multi-granular linguistic information in order to manage information provided by different experts. A practical transformation approach is developed, which makes numerical values expressed in two-tuple linguistics and further converted into values in [0, 1] interval. Compared with the traditional MAGDM model, a tri-level decision making model …that includes a top DM, multiple middle level DMs and multiple experts is considered. A novel mathematical programming model is constructed considering all middle level DMs’ preference information and regret aversion. Finally, an illustrative example is given to verify the proposed method. The results and comparative analysis demonstrate its effectiveness and practicability. Show more

Keywords: Tri-level decision making, multi-attribute group decision making, linguistic two-tuples, multi-granular, regret theory

DOI: 10.3233/JIFS-171309

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 793-806, 2018

Authors: Sharma, Rika | Verma, Kesari

Article Type: Research Article

Abstract: Rainfall prediction is one of the complex nonlinear dynamic phenomena. This is due to uncertainties associated with the climatic parameters used for rainfall prediction. Fuzzy system has the capability to deal with the uncertainties and is efficient when the conventional linear statistical models are not able to perform well due to the nonlinear nature of the climatic parameters. In the present study, a data driven Fuzzy Inference System for high-dimensional data is developed to predict rainfall of the Indian subcontinent. Indian monsoon is an important climatic phenomenon due to its direct impact on socio-economic growth. The parameters Sea Surface Temperature, …Sea Level Pressure, El Niño-Southern Oscillation, Indian Ocean Dipole Mode and the Equatorial Indian Ocean Oscillation have been used for analyses and prediction. The variability of Indian rainfall is considered for the period of 25 years from 1990–2014 and the possibility of prediction is explored using Fuzzy Inference System. In fuzzy inference system the membership functions are the building blocks and computing its range is a crucial task. We have used triangular membership function and in order to define the range of membership function, this study proposes two methods, divisive method for input parameters and clustering based method for output parameter. The experimental results obtained using the proposed fuzzy inference system is compared with Multiple Linear Regression and Multiple Adaptive Regression Splines. The proposed Fuzzy based predictive model shows better results in terms of the accuracy with 84% and correlation 0.78 between actual and predicted rainfall. Show more

Keywords: Fuzzy Inference System, MLR, MARS, climate parameters, climate Indices and Correlation

DOI: 10.3233/JIFS-171325

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 807-821, 2018

Authors: Ning, Tao | Jin, Hua

Article Type: Research Article

Abstract: In order to solve the multi-objective flexible job-shop scheduling problem, a novel cloud bacterial foraging optimization algorithm is proposed. In this paper, the simulation model is established to maximize the makespan and the workload of machines. The optimal bacterial individuals can preserve curing position to additional turning and the common ones swim to the direction of them to absorb location information. The cloud crossover operator and cloud mutation operator are designed to avoid the shortcoming of premature convergence. The proposed method is verified to be more effective than other existing algorithms to solve the multi-objective FJSP through the example of …Kacem and testing of 6 workpieces× machines in a mould job-shop. Show more

Keywords: Multi-objective flexible job-shop scheduling, cloud computing, bacterial foraging optimization, crowding distance

DOI: 10.3233/JIFS-171391

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 823-829, 2018

Authors: Sreenu, Karnam | Malempati, Sreelatha

Article Type: Research Article

Abstract: Task scheduling on heterogeneous data centers of cloud computing environment is a challenging problem. The efficiency of the cloud depends on the adopted task scheduling strategy. The task scheduling algorithm schedules the required task resources of application in the cloud platform. Even though many algorithms are presented for task scheduling; they consider only the minimum objectives for the trade-off of optimal scheduling. In this paper, a multi-objective task scheduling strategy is proposed for the task scheduling problem in the cloud network as an NP-hard optimization problem. In order to solve the scheduling problem, Fractional Grey wolf Multi-objective optimization-based Task Scheduling …strategy (FGMTS) is newly proposed for scheduling tasks in the cloud. The proposed FGMTS algorithm is the combination of the existing fractional theory and Grey Wolf Optimizer algorithm. Also, the multi-objective function is newly formulated to solve the multi-objective scheduling problem. The fitness function for the proposed optimization considers the parameters, such as Execution time, Communication time, Execution cost, Communication cost, Energy, and Resource utilization for optimal scheduling. The experimentation of the proposed task scheduling strategy is carried out over two cloud setups. The performance of proposed system is validated over the existing techniques, such as PSO, GA, and GWO using the metrics considered in the multi-objective formulation function. The experimental results show that the proposed FGMTS-Task scheduling scheme allocates the resource for all incoming task requests while preserving the performance of the cloud with an increase in the profit. Show more

Keywords: Cloud computing, task scheduling, fractional theory, grey wolf optimization algorithm, multi-objectiveconstraints

DOI: 10.3233/JIFS-17148

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 831-844, 2018

Authors: Nadjafi, Mohammad | Farsi, M.A. | Jabbari Khamnei, H.

Article Type: Research Article

Abstract: The aim of this paper is introducing a method based on Fuzzy Time-To Failure (FTTF) to improve reliability analysis of complex engineering systems based on fault tree analysis. This method focuses on the quantitative part of fault trees (either static or dynamic) analysis and will compute failure probabilities. FTTF model is developed to estimate the reliability of system and solve aforetime methods problems. The presented FTTF model is able to figure out any construction consist of static and dynamic gates with FTTF distributions integrated on Fuzzy Monte Carlo Simulation (FMCS) techniques to analyzing Possibilistic functions associated with the fuzzy probability …distributions for each basic event. Using fuzzy algorithm, gates FTTF are generated, and Top-event TTF evaluated. Some case studies are used to demonstrate the priority of this method in exact evaluation in compared with other solving methods (like: BN, Analytical solution, Markov chain and traditional fuzzy fault tree modeling), but has much less effort while having higher accuracy. Finally, this model is implemented in an Emergency Detection System (EDS) which is a useful system in aerospace and space applications. Show more

Keywords: Reliability assessment, fault tree, fuzzy time-to-failure, fuzzy failure distribution, fuzzy monte carlo simulation, emergency detection system

DOI: 10.3233/JIFS-171491

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 845-859, 2018

Authors: Shin, Sungtae | Tafreshi, Reza | Langari, Reza

Article Type: Research Article

Abstract: This study focuses on a myoelectric interface that controls a robotic manipulator via neuromuscular electrical signals generated when humans make hand gestures. The proposed system recognizes dynamic hand motions, which change shapes, poses, and configuration of a hand over time, in real-time. Varying muscle forces controls the activation/inactivation modes. Gradients of a limb orientation give directions of movements of the robot arm. Classified dynamic motions are used to change the control states of the HCI system. The performance of the myoelectric interface was measured in terms of real-time classification accuracy, path efficiency, and time-related measures. The usability of the developed …myoelectric interface was also compared to a button-based jog interface. A total of sixteen human subjects were participated. The average real-time classification accuracy of the myoelectric interface was over 95.6%. The path efficiency of the myoelectric interface of the majority of the subjects showed similar performance to that of the jog interface. The results of the jog interface in the time-measures outperformed the results of the myoelectric interface. However, with the consideration of the overall advantages of the myoelectric interface, the decrease in the time-related performances may be offset. Show more

Keywords: Human computer interaction (HCI), gesture recognition, electromyography (EMG), myoelectric classification

DOI: 10.3233/JIFS-171562

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 861-876, 2018

Authors: Çevik, Cüneyt | Eminoğlu, Şehla

Article Type: Research Article

Abstract: We generalize the concept of fuzzy metric space in the sense of George and Veeramani by presenting the definition of generated fuzzy metric space and generated fuzzy bonded metric space. We prove also some known results of metric spaces including Baire’s theorem for generated fuzzy metric spaces through α -defective diameter.

Keywords: Generated metric space, generated fuzzy metric space, fuzzy diameter, generated fuzzy diameter

DOI: 10.3233/JIFS-171591

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 877-885, 2018

Authors: Eghdami, Hossien | Estaji, Ali Akbar | Haghdadi, Toktam

Article Type: Research Article

Abstract: In this paper, we introduce the notion of reference point, lower and upper approximation with respect to reference point by a Lie algebra. We are concerned with some important properties of them. For a fuzzy Lie subalgebra μ of a Lie algebra L , t -level relation U  (μ , t ) : = {(x , y ) ∈ L  × L  : μ  (x  - y ) ≥ t , μ  ([x , y ]) ≥ t } on L , and t -level relation with respect to the reference point a , U e  (μ , t , a ) : = {(x , y ) ∈ L  × L  : μ  ([a , …x  - y ]) ≥ t }, are equivalence relations on L , for every t  ∈ [0, 1] and every a  ∈ L . We study lower and upper approximation with respect to the equivalence relations U  (μ , t ) and U e  (μ , t , a ) on a Lie algebra L , for every t  ∈ [0, 1] and every a  ∈ L . Furthermore, we show that if μ is a fuzzy Lie subalgebra of a Lie algebra L , a  ∈ L and t  ∈ [0, 1] then Fix ¯ ( U ( μ , t ) ) , Fix _ ( U ( μ , t ) ) , Fix ¯ ( U e ( μ , t , a ) ) and Fix _ ( U e ( μ , t , a ) ) are distributive complete lattices with respect to inclusion, where Fix _ ( θ ) ( Fix ¯ ( θ ) ) stand for the set of fixed points of upper (lower) equivalence relation θ . Also we obtain some relationship between ideals of a Lie algebra L and rough ideals with respect to the equivalence relations U e  (μ , t , a ) on L . Show more

Keywords: Rough set, fuzzy Lie algebra, reference point, Lie ideal, fixed point

DOI: 10.3233/JIFS-171620

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 887-899, 2018