Journal of Intelligent & Fuzzy Systems - Volume 24, issue 2

Authors: Mortaji, Seyed Taha Hossein | Bagherpour, Morteza | Noori, Siamak

Article Type: Research Article

Abstract: Earned Value Management (EVM) is a well-known project management technique to measure project performance and progress in a significant manner. The EVM has an ability to simultaneously and actively monitor and manage scope, schedule, and cost status via an integrated system. In this paper, firstly, we have formulated EVM in vagueness environment using L-R fuzzy numbers. It improves applicability of the EVM under real-life and uncertain conditions and leads to better planning and taking more appropriate managerial decisions. Also, it overcomes the typical fuzzy numbers' drawbacks. Besides, an efficient approach to calculate estimate at completion (EAC) has been developed. Finally, …an illustrative case proves successful implementation of the proposed method in reality. Show more

Keywords: Fuzzy earned value, uncertainty, L-R fuzzy number, fuzzy progress, estimate at completion

DOI: 10.3233/IFS-2012-0556

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 2, pp. 323-332, 2013

Authors: Mahmoudi, Maryam Tayefeh | Beheshti, Maedeh | Taghiyareh, Fattaneh | Badie, Kambiz | Lucas, Caro

Article Type: Research Article

Abstract: Content-based image retrieval (CBIR), as a well-known retrieval method, has been widely used in various applications. The basis of this method is on features like color, texture and shape. Color image histograms are very useful tools for this purpose. As these kinds of histograms results with large variations between neighboring bins, they seem so sensitive to any kind of changes such as noise, illumination, etc. To overcome this problem, fuzzy linking histogram based on OWA aggregation operator is proposed, which is capable of projecting 3-dimensional (L*a*b*) color histograms into single-dimension. The proposed method have been evaluated and compared with five …other methods in retrieving similar images from the common database. The experimental results, reveals better performance of the proposed method in comparison with the other mentioned methods. Show more

Keywords: Image retrieval, fuzzy color histogram, ordered weighted average (owa), fuzzy linking histogram

DOI: 10.3233/IFS-2012-0557

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 2, pp. 333-346, 2013

Authors: Derhami, Vali

Article Type: Research Article

Abstract: The sequential and uncontrolled punishments in social life may lead to what psychologists call learned helplessness or depression. Like learning in social life, agents based on Fuzzy Reinforcement Learning (FRL) sometimes cannot learn well. Experiments show that if an agent continuously performs actions that cause sequential punishments in the beginning of learning, then it does not usually behave well and often selects actions that evoke punishments. Therefore, the learning takes so long or not successful. In this paper, we address this issue called faulty learning in RL algorithm by exploiting learned helplessness. We demonstrate learned helplessness in the training of …an agent by FRL algorithm and analyze it. The result of analysis shows that since the action value function is approximated by a fuzzy system; continuous punishments lead all weight parameters of the approximator toward negative amounts. Hence, the agent cannot learn well. To prevent this problem, we propose a new reinforcement function. The proposed reinforcement function is adaptive and depends on the number of visit of the state. Simulation results show that new reinforcement function prevents learned helplessness and improves the learning in terms of learning speed and action quality. The proposed ideas can be used and extended to our social and psychology life. Show more

Keywords: Learned helplessness, fuzzy systems, reinforcement learning, Sarsa

DOI: 10.3233/IFS-2012-0558

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 2, pp. 347-354, 2013

Authors: Datta, Somak | Pratihar, D.K. | Bandyopadhyay, P.P.

Article Type: Research Article

Abstract: A novel architecture of hierarchical adaptive neuro-fuzzy inference systems was developed, which was tuned using a genetic algorithm and particle swarm optimization algorithm, separately. It was used to establish input-output relationships of a plasma spray coating process. The parameters, namely primary gas flow rate, stand-off distance, powder flow rate and arc current were considered as inputs of the process and the quality of coating was represented using three responses, such as its thickness, porosity and microhardness. Particle swarm optimization-based approach was found to perform better than the genetic algorithm-based approach on some test cases.

Keywords: Plasma spray coating, adaptive neuro-fuzzy inference system, hierarchical structure, genetic algorithm, particle swarm optimization

DOI: 10.3233/IFS-2012-0560

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 2, pp. 355-362, 2013

Authors: Hadi, Mahdipour | Morteza, Khademi | Hadi, Sadoghi Yazdi

Article Type: Research Article

Abstract: Many variants of fuzzy c-means (FCM) clustering method are applied to crisp numbers but only a few of them are extended to non-crisp numbers, mainly due to the fact that the latter needs complicated equations and exhausting calculations. Vector form of fuzzy c-means (VFCM), proposed in this paper, simplifies the FCM clustering method applying to non-crisp (symbolic interval and fuzzy) numbers. Indeed, the VFCM method is a simple and general form of FCM that applies the FCM clustering method to various types of numbers (crisp and non-crisp) with different correspondent metrics in a single structure, and without any complex calculations …and exhaustive derivations. The VFCM maps the input (crisp or non-crisp) features to crisp ones and then applies the conventional FCM to the input numbers in the resulted crisp features' space. Finally, the resulted crisp prototypes in the mapped space would be influenced by inverse mapping to obtain the main prototypes' parameters in the input features' space. Equations of FCM applied to crisp, symbolic interval and fuzzy numbers (i.e., LR-type, trapezoidal-type, triangular-type and normal-type fuzzy numbers) are obtained in this paper, using the proposed VFCM method. Final resulted equations are the same as derived equations in [7, 9, 10, 13, 18, 19, 30, 38–40] (the FCM clustering method applying to non-crisp numbers directly and without using VFCM), while the VFCM obtains these equations using a single structure for all cases [7, 9, 10, 13, 18, 19, 30, 38–40] without any complex calculations. It is showed that VFCM is able to clustering of normal-type fuzzy numbers, too. Simulation results approve truly of normal-type fuzzy numbers clustering. Show more

Keywords: Vector fuzzy c-means, crisp, symbolic interval and fuzzy numbers, clustering

DOI: 10.3233/IFS-2012-0561

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 2, pp. 363-381, 2013

Authors: Khooban, Mohammad Hassan | Soltanpour, Mohammad Reza

Article Type: Research Article

Abstract: This paper provides an optimal controlling approach for a class of nonlinear systems with structured and unstructured uncertainties using fuzzy sliding mode control. First known dynamics of the system are eliminated through feedback linearization and then optimal fuzzy sliding mode controller is designed using an intelligent fuzzy controller based on Sugeno-Type structure. The proposed controller is optimized by a novel heuristic algorithm namely Particle Swarm Optimization with random inertia Weight (RNW-PSO). In order to handle, the uncertainties Lyapunov method is used. There are no signs of the undesired chattering phenomenon in the proposed method. The globally asymptotic stability of the …closed-loop system is mathematically proved. Finally, this control method is applied to the inverted pendulum system as a case study. Simulation results show desirability of the system performance. Show more

Keywords: Nonlinear system, uncertainties, optimal, fuzzy, sliding mode control

DOI: 10.3233/IFS-2012-0569

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 2, pp. 383-394, 2013

Authors: Wang, Rui-Zhi | Miao, Duo-Qian | Xu, Fei-Fei | Zhang, Hong-Yun

Article Type: Research Article

Abstract: The quantitative analysis of the degree of knowledge granularity poses theoretical challenges for the development of granular computing. Information-theoretic measures have been proposed to address this problem, which exhibit usefulness in complete information systems. However, mathematical analysis of relationships between these information-theoretic measures and knowledge granularity has not been done. In this paper, after introducing Shannon's entropy and mutual information into complete information systems, we prove, for the first time, that these information-theoretic measures decrease monotonously as partition becomes coarser under complete information systems. Moreover, we illustrate that their inverse relationships do not hold generally and present an additional condition …under which the inverse relationships are valid. By generalizing Shannon's entropy to incomplete information systems, we further discuss the relationship between the generalized Shannon's entropy (termed as rough information entropy) and knowledge granularity based on covering generalized rough sets. We find that in incomplete information systems, the rough information entropy varies nonmonotonously as covering becomes coarser. An illustrative example is given to verify the above observation result. Show more

Keywords: Granular computing, information entropy, rough sets, complete information systems, incomplete information systems

DOI: 10.3233/IFS-2012-0570

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 2, pp. 395-404, 2013

Authors: Liu, Peide

Article Type: Research Article

Abstract: With respect to the multi-attribute group decision-making problems in which the attribute values and attribute weights take the form of the interval grey linguistic variables, the multi-attribute group decision making method based on the interval grey linguistic variables weighted aggregation operator is proposed. Firstly, the operation rules, the properties, and the comparing method of the interval grey linguistic variables are defined. Then some aggregation operators are defined, such as interval grey linguistic weighted aggregation (IGLWA) operator, interval grey linguistic ordered weighted aggregation (IGLOWA) operator, and interval grey linguistic hybrid weighted aggregation (IGLHWA) operator; the decision making methods based on these …operators are proposed to solve the group decision making problems. Finally, a numerical example is used to illustrate the use of the proposed method. The result shows the approach is simple and effective. Show more

Keywords: Grey fuzzy number, interval grey linguistic variables, the interval grey linguistic variables hybrid weighted aggregation operator, multi-attribute group decision making

DOI: 10.3233/IFS-2012-0572

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 2, pp. 405-414, 2013