Journal of Intelligent & Fuzzy Systems - Volume 27, issue 3

Authors: Lin, Yong | Xu, Jiaqing | Makedon, Fillia

Article Type: Research Article

Abstract: The purpose of evidence inference is to judge truth values of the environment states under uncertain observations. This has been modeled as mathematical problems, using Bayesian inference, Dempster-Shafer theory, etc. After formalizing judgment processes in evidence inference, we found that the judgment process under uncertainty can be modeled as a Bayesian game of subjective belief and objective evidence. Another, the rational judgment involves a perfect Nash equilibrium. Evidence equilibrium is the Nash equilibrium in judgment processes. It helps us to maximize the possibility to avoid bias, and minimize the requirement for evidence. This will be helpful for the dynamic analysis …of uncertain data. In this paper, we provide an Expected k-Conviction (EkC) algorithm for the dynamic data analysis based on evidence equilibrium. The algorithm uses dynamic evidence election and combination to resolve the estimation of uncertainty with time constraint. Our experimental results demonstrate that the EkC algorithm has better efficiency compared with the static evidence combination approach, which will benefit realtime decision making and data fusion under uncertainty. Show more

Keywords: Bayesian game, Dempster-Shafer, Nash equilibrium, data fusion

DOI: 10.3233/IFS-141120

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 3, pp. 1533-1543, 2014

Authors: Norkey, Gavendra | Dubey, Avanish Kumar | Agrawal, Sanat

Article Type: Research Article

Abstract: Duralumin is an alloy of aluminium which has some unique properties such as high strength to weight ratio, high resistance to corrosion, light in weight, and more demanding alloy in various sectors such as space craft, marine, chemical industries, construction and automobile. These applications require very precise and complex shapes which may not be obtained with conventional machining. Pulsed Nd:YAG laser cutting may be used to fulfill these objectives by using optimum setting of process parameters. The present research paper has experimentally investigated the modeling and optimization of heat affected zone in the pulsed Nd:YAG laser cutting of Duralumin sheet …with the aim to minimize heat affected zone. The quality is improved by the proper control of different process parameters such as gas pressure, pulse width, pulse frequency and scanning speed. Artificial intelligence (AI) algorithms have been used to solve the many engineering problems successfully through development of Genetic Algorithm (GA), Fuzzy Logic (FL) and Artificial Neural Network (ANN) systems. The optimization of heat affected zone has been carried out by using Hybrid Approach of Multiple Regression Analysis (MRA) and GA. In this methodology, the second order regression model has been developed by using MRA with the help of experimental data obtained by L27 orthogonal array (OA). Further this equation has been used as objective function in GA based optimization. The significant factors have been found with further discussion of their effect on the heat affected zone. Show more

Keywords: Laser cutting, duralumin sheet, heat affected zone, modeling and optimization, genetic algorithm

DOI: 10.3233/IFS-141121

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 3, pp. 1545-1555, 2014

Authors: Forouzesh, Fereshteh | Eslami, Esfandiar | Borumand Saeid, Arsham

Article Type: Research Article

Abstract: In this paper, we introduce two different stabilizers of X with respect to Y for subsets X and Y of an MV-algebra A. We show that stabilizers are ideals and we investigate the relation between stabilizers and some other ideals in MV-algebras. We also show that if I and J are ideals in an MV-algebra A, then the stabilizer of I with respect to J is the relative pseudo-complement of I with respect to J in the lattice of ideals of A.

Keywords: MV-algebra, stabilizer, ideal

DOI: 10.3233/IFS-141122

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 3, pp. 1557-1565, 2014

Authors: Golmaryami, Marjan | Saleh, Sadreddin | Ardekani, Abbas Bahaodini | Kavousi-Fard, Farzaneh

Article Type: Research Article

Abstract: Nowadays, the Distribution Feeder Reconfiguration (DFR) is known as a famous reinforcement technique to enhance the radial distribution abilities. So that the optimal management of DFR problem can lead to several profits such as load balance improvement, power loss reduction, voltage profile intensification, etc. Also, this paper aims to take the positive effect of the DFR strategy on the network performance under investigation. In this regard, an evolutionary algorithm based on bat algorithm (BA) is suggested to study the DFR problem deeply. The total active power losses, voltage deviation and load balance are considered as objective functions. Thus, a new …self-adaptive modification is implemented to search the multi-objective problem space globally. Other than that, in order to satisfy all the objective functions efficiently, a fuzzy-based interactive method is applied. This idea will give the operator the capability to decide the satisfying degree of each objective function. In the end, the proposed algorithm is tested on the 32-bus IEEE radial distribution system to demonstrate the feasibility and effectiveness of the method. Show more

Keywords: Distribution feeder reconfiguration, multi-objective optimization, fuzzy based interactive method, self-adaptive modified BA

DOI: 10.3233/IFS-141123

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 3, pp. 1567-1573, 2014

Authors: Badar, Rabiah | Khan, Laiq

Article Type: Research Article

Abstract: A novel adaptive control strategy to control the nonlinear dynamic plants is proposed in this article. The proposed Hybrid Adaptive NeuroFuzzy Bspline based Wavelet Control (HABsWC) synergistically integrates the locally controllable Bspline membership functions and wavelets in the NeuroFuzzy architecture. The parameters of HABsWC are updated online using gradient descent based backpropagation algorithm and the stability is guaranteed by defining an upper bound on the learning rates using Lyapunov stability criteria. Some important considerations are presented highlighting the effectiveness of online sensitivity measure of plant in adaptive control law. By providing online sensitivity measure, the adaptive control law influences the …convergence of system states and smoothness of control effort. Electric power system, being highly nonlinear and non-stationary in nature, has been chosen as a plant for the application of HABsWC to damp power system oscillations using Static Synchronous Series Compensator (SSSC). The performance of the proposed control scheme is validated using different operating conditions and faults for Single Machine Infinite Bus (SMIB) test system. The performance comparison, based on nonlinear time domain simulations and different performance indices, reveals that the proposed control strategy improves the performance of SSSC to enhance the transient stability with increase in smoothness of control effort. Show more

Keywords: Wavelets, bspline, power system stability, adaptive neurofuzzy control, SSSC

DOI: 10.3233/IFS-141124

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 3, pp. 1575-1587, 2014

Authors: Naeem, Muhammad | Asghar, Sohail

Article Type: Research Article

Abstract: Bayesian Belief Network has inspired the community of machine learning in the domain of structure learning. Numerous scoring functions have been introduced in the structure learning. The performance of these scoring functions usually tends to favor the dense Bayesian Network by using an implicit over-fitting phenomenon. Motivated by this limitation, this study has introduced a novel scoring function which is optimized for producing non complex learnt structures but with the target of higher classification accuracy. The introduced scoring function assumes no external parameter for its fine tuning. It is decomposable and possesses no penalty factor. The introduced scoring function holds …its mathematical interpretation within information theory. This scoring function is designed to maximize the discriminant function for given dataset query variables with respect to the class feature and other non class features. The empirical evaluation of the introduced scoring function points out that its classification accuracy is significantly better than other existent scoring functions using greedy search algorithm K2 and hill climber. The outcome of this study illustrates that simplistic structure with higher classification performance is possible by means of exercising the proposed scoring function in the Bayesian Belief structure learning. Show more

Keywords: Bayesian belief network, machine learning, discriminative learning, scoring functions, hill climbing algorithm

DOI: 10.3233/IFS-141125

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 3, pp. 1589-1599, 2014

Authors: Baziar, Aliasghar | Rostami, Mohammad-Ali | Akbari-Zadeh, Mohammad-Reza

Article Type: Research Article

Abstract: This paper develops a new framework to solve the practical non-convex economic dispatch problem with regard to the constraints including ramp rate limits, valve loading effect, prohibited operating zone, spinning reserve and multi-fuel option. In the proposed framework, bat algorithm, as a new optimization algorithm, is employed to explore the problem search space globally. In addition, a newly introduced adaptive modification method is developed to improve the variety of the bat population when increasing the convergence speed simultaneously. This modification is constructed based on the roulette wheel mechanism in conjunction with the crossover and mutation operators from the genetic algorithm. …At the end of paper, the superiority of the proposed framework is examined using the IEEE 10-unit and 40-unit test systems. Show more

Keywords: Non-convex economic dispatch, modified bat algorithm, modification mechanism, non-linear constrained optimization

DOI: 10.3233/IFS-141126

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 3, pp. 1601-1607, 2014