Journal of Intelligent & Fuzzy Systems - Volume 28, issue 1

Authors: Husain, N.A. | Rahim, M.S.M. | Khan, A.R. | Al-Rodhaan, Mznah | Al-Dhelaan, Abdullah | Saba, T.

Article Type: Research Article

Abstract: Sub-devising a surface refers a process that is carried on polygon mesh to manufacture flat surfaces. Several subdivision schemes had been introduced before but are too consuming in terms of time and memory as it compute and render all of the vertices during the subdivision process. Adaptive subdivision, on the other hand subdivides only the required vertices of selected areas, and maintains the number of polygons for the rest of the meshes. However, the problem in this refinement operation usually happens at the upper level of the subdivision process, where the increased number of polygons led to heavy computational load. …This research proposed IteAS (Iterative Adaptive Subdivision Surface), an enhancement of the adaptive subdivision surface to tackle this problem and to further optimize memory consumption. The proposed method can reduce the number of polygons used in previous method by 9%, optimize memory consumption up to 7% and is able to produce smooth surface of 3D object. Show more

Keywords: Smooth surfaces, iterative subdivision surfaces, adaptive subdivision, area selected

DOI: 10.3233/IFS-141308

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 337-344, 2015

Authors: Senthil Babu, S. | Vinayagam, B.K.

Article Type: Research Article

Abstract: For a decade, surface roughness is considered as the main factor of product quality since it has a great influence on the performance of mechanical parts as well as production cost. Surface roughness has an impact on the mechanical properties like fatigue behavior, corrosion resistance, creep life, etc. There are various methods for measurement of surface roughness. They are direct measurement methods, comparison based techniques, non contact methods and on process measurement. The parameters which lead to surface roughness are cutting speed, feed rate, depth of cut, cutting environment, cutting tool wears and so on. In the drilling process, if …the speed becomes too high the tool will break and also if the speed becomes too low it will take a lot of time to complete the process and the production rate will go down. Thus, surface finish is an important factor to taken into account in the drilling process. So, it is more necessary to predict the surface roughness of the materials. A lot of researchers have been contributed in predicting the surface roughness of the materials. However, many of them failed since the input model and output categorization varies. Some of the research are ANN model for predicting surface roughness from machining parameters such as cutting speed, feed rate, and depth of cut. Another model is hybrid modeling approach, based on the group method of data handling and the differential evolution population-based algorithm, for modeling and predicting surface roughness in turning operations. But it is difficult to calculate the optimal cutting conditions for the considered material and tool. Also the neural network model coupled with the GA is proposed to determine the optimal machining for surface roughness. But, all these methods fail as there is a large variation in input model and output. Moreover, a recent research was conducted in predicting the surface roughness of materials. This predictive model of surface roughness is created by using back propagation neural network and EM (Electromagnetism) optimization algorithm is used to optimize the problem. The research showed that the EM algorithm coupled with back propagation neural network is an efficient and accurate method in obtaining the minimum of surface roughness. However, in order to further reduce the variation between input model and output, we proposed a feed forward neural network model using APSO (Adaptive particle swarm optimization) algorithm. Our proposed prediction model using APSO algorithm is a very efficient method in decreasing the variation between input model and output than the conventional PSO algorithm. Also, our proposed model minimizes the error to a greater extent than any other method. Show more

Keywords: Surface roughness, artificial neural network (ANN), particle swarm optimization (PSO) algorithm

DOI: 10.3233/IFS-141310

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 345-360, 2015

Authors: Izadikhah, Mohammad

Article Type: Research Article

Abstract: The evaluation and selection of the appropriate machine tools is one of the most critical decisions in the design and development of an efficient production environment and the use of fuzzy set theory allows incorporating qualitative and partially known information into the decision model. This paper describes a fuzzy goal programming method for evaluation and selection of machine tool alternatives for a manufacturing company in Iran. Our approach applied triangular numbers into traditional goal programming method, and we investigated deriving fuzzy weights of criteria from the pair-wise comparison matrix with fuzzy elements. To our knowledge, no previous work investigated such …problem with fuzzy goal programming. In almost fuzzy decision making problems other fuzzy methods like fuzzy AHP, fuzzy TOPSIS and etc. are used. And most of them obtained the crisp weights from fuzzy pair-wise decision matrix. Moreover, in this method we obtain the fuzzy weights by solving a simple linear programming. As a result of the study, we find that the proposed method is practical for ranking machine tool alternatives with respect to multiple conflicting criteria. Show more

Keywords: Machine tool selection, goal programming, fuzzy data, fuzzy weights, fuzzy pair-wise comparison matrix

DOI: 10.3233/IFS-141311

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 361-372, 2015

Authors: Haveshki, Masoud | Mohamadhasani, Mahboobeh

Article Type: Research Article

Abstract: We introduce the notion of α-filters in BL-algebras and then state and prove some theorems which determine the relationships of these filters and other filters in BL-algebras. Some properties of the lattice of all α-filters are investigated too.

Keywords: BL-algebra, α-filter, complete Browerian lattice, pseudocomplemented lattice, algebraic lattice

DOI: 10.3233/IFS-141313

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 373-382, 2015

Authors: Davodi, Abdolmohamad | Esapour, Khodakhast | Zare, Alireza | Rostami, Mohammad-Ali

Article Type: Research Article

Abstract: This paper aims to propose an effective intelligent optimization method to solve the multi-objective distribution feeder reconfiguration (DFR) problem considering distributed generations (DGs). In this regard, we introduce a novel population based algorithm based on krill herd (KH) algorithm to solve the multi-objective distribution feeder reconfiguration problem considering DG units. In order to improve the search ability of the algorithm, a new modification process is proposed too. This modification enhances the overall outcome of the KH algorithm in both search and convergence area. During the search process of the proposed modified KH (MKH) algorithm, the achieved non-dominated solutions are stored …in an external repository. Owing to distinctive objective functions, a fuzzy clustering technique is applied to control the size of the repository within the restrictions. The objective functions considered in this paper are power losses, voltage deviation of buses and total cost of the active power produced by DG units and distribution companies. In order to evaluate the feasibility and effectiveness of the method, the proposed approach is tested on a distribution test system. Show more

Keywords: Modified Krill Herd (MKH) Algorithm, multi-objective distribution feeder reconfiguration, distributed generation (DG), fuzzy clustering, non-dominated solution

DOI: 10.3233/IFS-141314

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 383-391, 2015

Authors: Van Hoa, Ngo | Van Tri, Phan | Dao, Tran Trong | Zelinka, Ivan

Article Type: Research Article

Abstract: In this paper, we establish the global existence and uniqueness results for fuzzy functional differential equations (FFDEs) by using two different methods. We have extended and generalized some comparison theorems and stability theorem for FFDEs with definition a new Lyapunov-like function. Some examples are given to illustrate these results.

Keywords: Fuzzy sets, fuzzy functional differential equations, strongly generalized Hukuhara derivative, stability theorems

DOI: 10.3233/IFS-141315

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 393-409, 2015

Authors: Hazarika, Bipan

Article Type: Research Article

Abstract: An ideal I is a family of subsets of positive integers $\mathbb{N}$ which is closed under taking finite unions and subsets of its elements. In this paper we introduce ideal convergent sequence spaces of fuzzy numbers using σ-bounded variation and Orlicz functions and study some basic topological and algebraic properties of these spaces. Finally we investigate the inclusions relations related to these spaces.

Keywords: Ideal, I-convergence, σ-bounded variation, Orlicz function

DOI: 10.3233/IFS-141317

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 411-420, 2015

Authors: Zare, Jafar | Zare, Alireza

Article Type: Research Article

Abstract: This article has been retracted. The pdf file of the article has been replaced with a retraction notice.

DOI: 10.3233/IFS-141318

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 421-431, 2015

Authors: Finotto, Vitor C. | da Silva, Wilson R. Leal | Valašek, Michael | Štemberk, Petr

Article Type: Research Article

Abstract: This paper proposes cabled-trusses benchmarks for mechanical engineering applications and provides suitable tools for modeling and optimization of cabled-trusses. These structures correspond to a system of cables and triangular bar formations jointed at their ends by hinged connections to form a rigid framework. The optimized cabled-truss is determined through a discrete optimization procedure that uses nonlinear finite element analysis, genetic algorithm, and fuzzy logic. In this work, planar and spatial trusses and cabled-trusses are optimized to achieve minimum weight designs. Also, the structural performance of the optimized structures is compared. In summary, the results show that cabled-trusses feature improvements over …trusses. Show more

Keywords: Cabled-truss, fuzzy logic, genetic algorithm, nonlinear finite element analysis, structural optimization

DOI: 10.3233/IFS-141319

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 433-446, 2015

Authors: Zare, Alireza | Kavousi-Fard, Abdollah | Abbasi, Alireza | Kavousi-Fard, Farzaneh

Article Type: Research Article

Abstract: With the high penetration of renewable power sources in the form of distributed generations (DGs), the amount of uncertainty in the power systems is increased greatly. This high uncertainty has affected most of the grid operation strategies including the optimal management of DGs. One significant source of uncertainty is the forecast error in the modeling of the future active and reactive load values. In order to deal with this problem, this paper suggests a new stochastic framework based on the scenario generation process and roulette wheel mechanism. This method converts the stochastic problem into a number of deterministic problems with …different probabilities. Since the problem investigated is a complex nonlinear optimization problem, a sufficient optimization algorithm based on the bio-inspired krill herd algorithm is proposed to solve the problem effectively. The satisfying performance of the proposed method is examined on the IEEE standard test system. Show more

Keywords: Uncertainty, Roulette Wheel Mechanism (RWM), krill herd algorithm, adaptive modification, Distributed Generation (DG)

DOI: 10.3233/IFS-141320

Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 447-456, 2015