Journal of Intelligent & Fuzzy Systems - Volume 29, issue 4

Authors: Abbasi, Alireza | Farahnakian, Ehsan | Abbasi, Somayeh | Abbasi, Mehdi | Faraji, Eshagh

Article Type: Research Article

Abstract: This article suggests a probabilistic framework based on Scenario production to take account the uncertainties in the optimal operation management of Micro Grids (MGs). The MG includes different renewable energy resources such as Wind Turbine (WT), Micro Turbine (MT), Photovoltaic (PV), Fuel Cell (FC) and one battery as the storage device. The suggested framework is based on scenario generation and Roulette wheel mechanism to generate different scenarios for handling the uncertainties of different parameters. It uses normal distribution function as a probability distribution function of random parameters. The uncertainties which are considered in this paper are grid bid changes, load …demand forecasting error and PV and WT output power productions. It is worthy to say that solving the MG problem for 24 hours of a day by considering different uncertainties and different constraints needs one powerful optimization method that can converge fast when it doesn’t fall in local optimum point. As a result, one Group Search Optimization (GSO) algorithm is introduced to prospect the total search space globally. The GSO algorithm is originated from group living of animals. Besides the GSO algorithm, one modification is also proposed for this algorithm. The proposed framework and method is implemented o one test grid-connected MG as a typical grid. Show more

Keywords: Uncertainty, scenario based method, Group Search Optimization (GSO), Modified Group Search Optimization (MGEO), renewable energy recourses, battery

DOI: 10.3233/IFS-151638

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1595-1606, 2015

Authors: Verma, Tina | Kumar, Amit | Appadoo, SS

Article Type: Research Article

Abstract: Li and Yang [D.F. Li and J. Yang, A difference-index based ranking bilinear programming approach to solving bimatrix games with payoffs of trapezoidal intuitionistic fuzzy numbers, Journal of Applied Mathematics 2013 (2013), 1–10] pointed out that there is no method in the literature for solving such bimatrix games in which payoffs are represented by intuitionistic fuzzy numbers and proposed a method for the same. In this paper, it is pointed out that Li and Yang have considered some mathematical incorrect assumptions in their proposed method. For resolving the shortcomings of Li and Yang’s method, a new method (named …as Mehar method) is proposed. Also, the exact optimal solution of the numerical problem, solved by Li and Yang by their proposed method, is obtained by the proposed Mehar method. Show more

Keywords: Bimatrix game, trapezoidal intuitionistic fuzzy numbers, difference-index based ranking, bilinear programming

DOI: 10.3233/IFS-151640

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1607-1618, 2015

Authors: Bulutsuz, Asli G. | Yetilmezsoy, Kaan | Durakbasa, Numan

Article Type: Research Article

Abstract: Coordinate measuring machines (CMM) have a vital and enduring role in the manufacturing process because of their easy adaptation to the systems and high measurement accuracy. Owing to the demand for high accuracy and shorter cycle times of measurement tasks, determining the measurement errors has become more important in precision engineering. Additionally, manufactured components are becoming smaller and tolerances becoming tighter, and therefore, demands for accuracy are increasing. For this reason, dynamic error modeling has become a topic of considerable importance for improving measurement accuracy, manufacturing decisions and process parameter selections. A number of factors such as process parameters, measurement …environment, measuring object, reference element, measurement equipment and set-up affect the measurement accuracy of CMM. Considering the complicated inter-relationships among a number of system factors, artificial intelligence-based techniques have become essential tools due to their speed, robustness and non-linear characteristics when working with high-dimensional data. In this study, a fuzzy logic-based methodology was implemented as an artificial intelligence approach for determining measurement errors related to the process parameters for coordinate measuring machines. A Mamdani-type fuzzy inference system was developed within the framework of a graphical user interface. Eight-level trapezoidal membership functions were employed for the fuzzy subsets of each model variable. The product and the centre of gravity methods were performed as the inference operator and defuzzification methods, respectively. The proposed prognostic model provided a well-suited method and produced promising results in predicting measurement errors by monitoring the process parameters such as optimum measuring point numbers, probing speed and probe radius. Show more

Keywords: Coordinate measuring machines, fuzzy logic, measurement accuracy, uncertainty

DOI: 10.3233/IFS-151641

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1619-1633, 2015

Authors: Hussain, Asim | Shabbir, Muhammad

Article Type: Research Article

Abstract: Concept of soft finite state machine is being introduced, which is based on soft set theory. Concepts of soft successor and soft immediate successor are introduced and some of their properties are studied. Notions of soft subsystem, soft submachine are given here. Finally direct product of soft machines is studied.

Keywords: Soft subsystem, soft submachine, strongly soft connected, Weakly soft connected

DOI: 10.3233/IFS-151642

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1635-1641, 2015

Authors: Raju, B. Deevena | Pandarinath, P. | Prasad, GS

Article Type: Research Article

Abstract: Image Reconstruction is an important fragment in image processing. It is used to reconstruct the image which is corrupted by noise or that has some scratched regions. In order to improve the reconstruction effectiveness of the existing methods a new image reconstruction technique based on DWT and IPSO is proposed in this paper. The proposed technique is composed two main stages (i) training stage (ii) investigation stage. In training phase, initially the input cracked image is reconstructed by the DWT (Discrete wavelet Transform) method by selecting optimal threshold value using well known optimization technique as IPSO (Improved Particle Swarm Optimization). …These selected threshold values are stored in the Threshold Database and they are subjugated in the image reconstruction process. In investigation stage, the threshold value is selected based on the crack level of the testing image. The proposed method is implemented in MATLAB with various cracked images. The performance of the IPSO and DWT based image reconstruction technique is checked with existing PSO and average filtering image reconstruction technique in order to prove the efficiency of the proposed method. However, our proposed methodology provides better intuitive and high-quality reconstructed image for the noisy images than the existing method, in terms of peak signal-to-noise ratio (PSNR). Show more

Keywords: Image reconstruction, Improved Particle Swarm Optimization (IPSO), Discrete Wavelet Transform (DWT), Peak Signal-to-Noise Ratio (PSNR)

DOI: 10.3233/IFS-151643

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1643-1652, 2015

Authors: Garg, Harish

Article Type: Research Article

Abstract: In designing phase of systems, design parameters such as component reliabilities and cost are normally under uncertainties. Although there have been tremendous advances in the art and science of system evaluation, yet it is very difficult to assess these parameters with a very high accuracy or precision. Therefore, to handle this issue, this paper presents an alternative approach for solving the multi-objective reliability optimization problem by utilizing the uncertain, vague and imprecise data. For this a conflicting nature between the objectives is resolved with the help of intuitionistic fuzzy programming technique by considering the nonlinear degree of membership and non-membership …functions. The resultant fuzzy multi-objective optimization problem is converted into single-objective optimization problem using the satisfaction functions with exponential weights. The optimal solution of the corresponding problem has been obtained with the cuckoo search algorithm. Finally, a numerical instance is presented to show the performance of the proposed approach. Show more

Keywords: Intuitionistic fuzzy optimization, cuckoo search, reliability optimization, membership functions

DOI: 10.3233/IFS-151644

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1653-1669, 2015

Authors: Rubio-Manzano, Clemente | Julián-Iranzo, Pascual

Article Type: Research Article

Abstract: This paper aims to incorporate a knowledge discovery technique into the Proximity-based Logic Programming paradigm in order to generate background knowledge (conceptual hierarchies) in a semi-automatic way which may lead to an efficient and desirable abstraction process among the symbols (representing concepts) from a first-order language and to the discovery of generalized relationship among them i.e. a logic-based framework with the capability of abstraction. This method makes use of the concept of λ -block characterizing the notion of equivalence when working with proximity relations. When the universe of discourse is composed of concepts which are related by proximity, the sets of …λ -blocks extracted from that proximity relation can be seen as hierarchical sets of concepts grouped by abstraction level. Then, each group (forming a λ -block) can be labeled, with user help, by means of a more general descriptor in order to simulate a generalization process based on proximity. Thanks to this process, the system can learn concepts that were unknown initially and reply to queries that it was not able to answer. The novelty of this work is that it is the first time a method, with analogous features to the one aforementioned, is implemented inside a fuzzy logic programming framework. Certainly, in order to check the feasibility of the method, we have developed a software tool which have been integrated into the Bousi~Prolog system. Finally, this work presents a method to get a set of recommended abstract descriptors by using WordNet. This allows to improve the original generalization mechanism, helping the user in the task of selecting a convenient abstraction. Also, the overall method can be seen as a technique that facilitates the tuning of term ontologies. Show more

Keywords: Fuzzy logic programming, attributed-oriented induction, proximity relations, discovery of generalized knowledge, WordNet

DOI: 10.3233/IFS-151645

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1671-1683, 2015

Authors: Rezaei, Mehdi | Tanakian, Mohammad Javad

Article Type: Research Article

Abstract: Digital video stabilization (DVS) allows acquiring video sequences without disturbing jerkiness, removing unwanted camera movements. A good DVS should remove the unwanted camera movements while maintains the intentional camera movements. In this article, we propose a novel real-time DVS algorithm with a short-delay. The proposed DVS compensates the camera jitters applying an adaptive fuzzy filter on the global motion of video frames. The adaptive filter is an infinite impulse response (IIR) non-causal filter which is tuned by a fuzzy system adaptively to the camera motion characteristics. The fuzzy system itself is also tuned during operation according to the amount of …camera jitters. The fuzzy system uses two inputs which are quantitative representations of the unwanted and the intentional camera movements. The global motion of video frames is estimated based on the block motion vectors which resulted by video encoder during motion estimation operation. Experimental results indicate a good performance for the proposed algorithm. Show more

Keywords: Adaptive, delay, digital video stabilization, fuzzy filter, motion vector, video coding, numerical assessment

DOI: 10.3233/IFS-151646

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1685-1696, 2015

Authors: Wu, Hua | Su, Xiuqin

Article Type: Research Article

Abstract: Interval-valued intuitionistic fuzzy numbers (IVIFNs) are usually utilized in multi-attribute decision making problems, providing an accurate description of incomplete and uncertain information. The existing IVIFN-based works mainly focus on either the prioritization relationship of attributes or both the importance and the ordered position of them. However, these aspects of attributes are all important in practical use and they should be simultaneously considered. To this end, this paper proposes an interval-valued intuitionistic fuzzy prioritized hybrid weighted aggregation (IVIF-PHWA) operator. The contribution of this paper is threefold: 1) A unit prioritized hybrid weighted aggregation (UPHWA) operator is proposed, which considers the prioritization …relationship, the importance and the ordered position of attributes. 2) The UPHWA operator is extended into IVIF-PHWA operator, whose properties are all investigated. These properties illustrate that the IVIF-PHWA operator can better deal with the incomplete and imprecise information. 3) This work develops an IVIF-PHWA operator-based multi-attribute decision making method to solve the decision making problems in IVIF environment. Finally, a practical example is provided to validate the efficiency and effectiveness of the proposed approach. Show more

Keywords: Interval-valued intuitionistic fuzzy set, multi-attribute decision making, hybrid weighted aggregation operator, prioritization relationship

DOI: 10.3233/IFS-151647

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1697-1709, 2015

Authors: Yang, Yong | Liang, Chencheng | Ji, Shiwei | Liu, Tingting

Article Type: Research Article

Abstract: In this work, we first define picture fuzzy soft sets and study some of their relevant properties, especially, a sufficient and necessary condition is presented to ensure that the dual laws are true in picture fuzzy soft theory. We then introduce an algorithm based on adjustable soft discernibility matrix by using level soft set of a picture fuzzy soft set to solve decision making problems, which can find an order relation of all the objects. Finally, an illustrative example is employed to show that they can be successfully applied to problems that contain uncertainties.

Keywords: Soft set, Picture fuzzy set, picture fuzzy soft set, soft discernibility matrix, decision making

DOI: 10.3233/IFS-151648

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1711-1722, 2015