Journal of Intelligent & Fuzzy Systems - Volume 29, issue 6

Authors: Yu, Mingjiu | Qu, Min | Hu, Jun

Article Type: Research Article

Abstract: Designer thinking has received much attention as an innovative problem-solving approach. However, it is also a vague and unclear activity which can only be studied through the input and output results in a design process. This paper proposes that the visual design state is the external performance of design thinking, which is used to clarify vague design thinking. In this paper, a method for expressing and capturing design states based on multi-fuzzy cognitive mapping is presented. First, an agent model is built to capture the design states, and the weight values of the multi-fuzzy cognitive map matrix are calculated. The …tightness of the design state route is then deduced. An example is presented to demonstrate the use of this method, which is able to support the designer with the necessary design resources and an intelligent design environment. Show more

Keywords: Design state, tightness of design route, multi-fuzzy cognitive map (MFCM)

DOI: 10.3233/IFS-151970

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2669-2675, 2015

Authors: Yuan, Xia | Tang, Xiangyan | Zhao, Chunxia

Article Type: Research Article

Abstract: Road detection is still full of challenge for a small ground mobile robot with limited load capacity and computing resources which works in complex outdoor environment. This paper proposes a road detection method based on fuzzy support vector machine with on-line updating and retraining strategy. The algorithm extracts multi feature in image and trains a fuzzy support vector machine road classifier off-line by using few training samples. Then it detects road in laser points using a fuzzy clustering method based on maximum entropy principle. After calibrating the camera and laser range finder, and project laser points into the image, the …algorithm chooses road samples with high confidence automatically according to range data and designs a rule to retraining the FSVM on-line when needed to improve its environmental adaptability. Experiments in outdoor campus environment indicate that the proposed algorithm is effective. Show more

Keywords: Road detection, image segmentation, fuzzy support vector machine, maximum entropy principle, robotics

DOI: 10.3233/IFS-151971

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2677-2688, 2015

Authors: Wei, Ming | Chen, Xuewu | Sun, Bo | Zhu, Yao-Yao

Article Type: Research Article

Abstract: Regional bus scheduling is necessary to urban public transport that is complicated by the necessity of assigning trips that belong to several routes to buses located at different depots while reducing fleet size and operating costs. Considering the reality of emergencies that may interfere with the ability of vehicles to complete trips on time, it is reasonable to use fuzzy numbers to express uncertain delay times. Based on this idea, this paper proposes a chance-constrained programming model of regional bus scheduling that will reflect additional constraints such as the capacities of related depots and fueling needs. The objective of this …paper is to maximize utilization of fleet vehicles. To overcome the defect of premature convergence in the particle swarm optimization algorithm (PSO), an improved PSO is proposed by using an organic fusion with group search optimization. Finally, an example demonstrates the correctness and effectiveness of the model and algorithm. Show more

Keywords: Urban traffic, regional bus scheduling problem, fuzzy travel time, particle swarm optimization, group search optimization

DOI: 10.3233/IFS-151972

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2689-2696, 2015

Authors: Aiwu, Zhao | Jianguo, Du | Hongjun, Guan

Article Type: Research Article

Abstract: Neutrosophic sets are powerful logics designed to facilitate understanding of indeterminate and inconsistent information; many types of incomplete or complete information can be expressed as interval valued neutrosophic sets (IVNSs). This paper proposes improved aggregation operation rules for IVNSs, and extends the generalized weighted aggregation (GWA) operator to work congruently with IVNS data. The aggregated results are also expressed as IVNSs, which are characterized by truth-membership degree, indeterminacy-membership degree, and falsity-membership degree. The proposed method is proved to be the maximum approximation to the original data, and maintains most of the information during data processing. Then, a method is proposed …to determine the ranking orders for all alternatives according to their comparative advantage matrices based on their general score, degree of accuracy and degree of certainty expressed by the aggregated IVNSs. Finally, a numerical example is provided to illustrate the applicability and efficiency of the proposed approach. Show more

Keywords: Interval valued neutrosophic sets, multi-attribute decision making, generalized weighted aggregation, fuzzy sets

DOI: 10.3233/IFS-151973

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2697-2706, 2015

Authors: Li, Hui-Jia

Article Type: Research Article

Abstract: The analysis of fuzzy(overlapping) community structure in complex networks is an important problem in data mining of network data sets. However, due to the exist of random factors and error edges in real networks, how to measure the significance of community structure efficiently is a crucial question. In this paper, we present a novel statistical framework comparing the significance of fuzzy community structure across various optimization models. Different from the universal approaches, we calculate the similarity between a given node and its leader and employ the distribution of link tightness to derive the significance score, instead of a direct comparison …to a randomized model. Based on the distribution of community tightness, a new “p -value” form significance measure is proposed for community structure analysis. Specially, the well-known approaches and their corresponding quality functions are unified to a novel general formulation, which facilitate providing a detail comparison across them. To determine the position of leaders and their corresponding followers, an efficient algorithm is proposed based on the spectral theory. Finally, we apply the significance analysis to some famous benchmark networks and the good performance verified the effectiveness and efficiency of our framework. Show more

Keywords: Fuzzy community, statistical significance, optimization methods, quality functions, benchmark networks

DOI: 10.3233/IFS-151974

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2707-2715, 2015

Authors: Feng, Nan | Yu, Xue | Dou, Runliang | Pan, Bingning

Article Type: Research Article

Abstract: Risk management for business processes is critical to the survival and performance of organizations, and has gained the interest of practitioners and academics. In this article, a fuzzy based multi-agent system (FMAS) is proposed as a practical solution to assess the process risk state and provide recommendations for the continuous improvement of business processes. To represent uncertain and ambiguous information obtained from experts, fuzzy theory is introduced to the FMAS. A fuzzy neural network is employed to implement an analysis agent capable of detecting the risk state of business processes within a firm. Furthermore, based on the predictions yielded by …the analysis agent, the recommendation agent is then able to identify the possible deviations in the inconsistent process and provide suggestions for improvement. The effectiveness of the proposed FMAS is validated by its implementation in nine firms during twelve months, and the results are presented. Show more

Keywords: Multi-agent system, business process, risk management

DOI: 10.3233/IFS-151975

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2717-2726, 2015

Authors: Zhang, Cong | Wang, Heng

Article Type: Research Article

Abstract: Three-dimensional sound effects require a considerable number of sound channels, causing audio-visual spatial orientation sense distortion under circumstances in which the code rate is restricted by the limitation of transmission channel bandwidth and storage capacity. As a result, existing 3D audio systems are incompatible with real-time broadcasting and home theatre applications, severely limiting the application and development of 3D audio systems. By investigating the mechanism of orientation parameters perceptual redundancy, this paper studied 3D spatial orientation cue perceptual characteristics, established an orientation cue perceptual model, developed a heterogeneous quantification table accordingly, and controlled the differences between each quantified value below …the quantitative value perception threshold. Using this method, only the information perceptible to the human ear was quantified and perceptual distortions were minimized. The experimental results revealed that, compared to the SLQP method, the quantified bit of the proposed method was reduced by 8.66% in low resolution and 65.23% in high resolution. In addition, the accuracy of this method was higher than that of the SLQP method, enabling better alignment with human perceptual characteristics. Show more

Keywords: 3D Audio, orientation cue, perceptual characteristic, parameter coding

DOI: 10.3233/IFS-151976

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2727-2736, 2015

Authors: Xu, Hao | Xing, Lining | Huang, Lan

Article Type: Research Article

Abstract: Scientific and technological papers play a fundamental role in the scientific and technological innovation of countries. The quality control of scientific and technological articles is vital to the journals and management of personnel. This paper investigates multiple attribute decision-making problems with the application of hesitant fuzzy uncertain linguistic information. Motivated by the ideal traditional I-COA operator, an induced hesitant fuzzy uncertain linguistic correlated averaging (IHFULCA) operator is developed. The IHFULCA operator was used to develop approaches to solve hesitant fuzzy uncertain linguistic multiple attribute decision-making problems. Finally, a practical example for evaluating the academic value of scientific and technological papers …is provided to verify the developed approach and demonstrate its practicality and effectiveness. Show more

Keywords: Multiple attribute decision-making, hesitant fuzzy uncertain linguistic values, scientific publications

DOI: 10.3233/IFS-151977

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2737-2742, 2015

Authors: Yu, Jing | Yu, Qi

Article Type: Research Article

Abstract: A conflict analysis framework with fuzzy preference can be utilized to model and analyze conflicts in which decision makers (DMs) hold unclear or ambiguous preferences. One important function of this framework is that it can predict different conflict resolutions based on DMs’ different fuzzy satisficing thresholds. The fuzzy preference conflict analysis framework extends the option prioritization technique that can efficiently elicit DMs’ crisp preferences, also using it to calculate DMs’ fuzzy preferences. Through analyzing a water pollution conflict that occurred between the upstream and the downstream areas of a reservoir in China, the capability of the fuzzy preference conflict analysis …framework to investigate real-world conflicts is verified, as is the efficiency of the fuzzy option prioritization methodology in representing DMs’ fuzzy preferences. Show more

Keywords: Conflict analysis, fuzzy preference, option prioritization, water pollution conflict

DOI: 10.3233/IFS-151978

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2743-2749, 2015

Authors: Yoon, Heejin | Lim, Jongwoo | Lim, Joon S.

Article Type: Research Article

Abstract: As a reverse engineering field, reconstructing a Gene Regulatory Network (GRN) from time series gene data has been a challenging issue in bioinformatics. This paper proposes a novel engineering framework that infers and reconstructs a gene regulatory network in terms of regulatory accuracy. Different from other statistical methods, the proposed framework uses features that represent the characteristics of time series datasets and selects the appropriate features of the time series data by using a neuro-fuzzy system. The proposed framework for reconstruction is based on a Neuro Network with Weighted Fuzzy Membership Function (NEWFM), which not only simplifies fuzzy inference and …regulation model complexity but also improves the regulatory accuracy of reconstructing the GRN without minimizing the dynamic regulatory cycle. Finally, the proposed framework is evaluated with experimental results that demonstrate higher regulatory accuracy than previous algorithms. Show more

Keywords: Gene regulatory networks, microarray data, time series, neuro-fuzzy systems

DOI: 10.3233/IFS-151979

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2751-2757, 2015