Journal ArticleDOI
An approach for analyzing the reliability of industrial systems using soft-computing based technique
Reads0
Chats0
TLDR
A novel technique for analyzing the behavior of an industrial system by utilizing vague, imprecise, and uncertain data and an artificial bee colony has been used for determining their corresponding membership functions.Abstract:
The purpose of this paper is to present a novel technique for analyzing the behavior of an industrial system by utilizing vague, imprecise, and uncertain data. In this, two important tools namely traditional Lambda-Tau and artificial bee colony algorithm have been used to build a technique named as an artificial bee colony (ABC) algorithm based Lambda-Tau (ABCBLT). In real-life situation, data collected from various resources contains a large amount of uncertainties due to human errors and hence it is not easy to analyze the behavior of such system up to a desired accuracy. If somehow behavior of these systems has been calculated, then they have a high range of uncertainty. For handling this situation, a fuzzy set theory has been used in the analysis and an artificial bee colony has been used for determining their corresponding membership functions. To strengthen the analysis, various reliability parameters, which affects the system performance directly, have been computed in the form of fuzzy membership functions. Sensitivity as well as performance analysis has also been analyzed and their computed results are compared with the existing techniques result. The butter-oil processing plant, a complex repairable industrial system has been taken to demonstrate the approach.read more
Citations
More filters
Journal ArticleDOI
Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment
TL;DR: A methodology for solving the multi-objective reliability optimization model in which parameters are considered as imprecise in terms of triangular interval data and a conflicting nature between the objectives is resolved.
Journal ArticleDOI
Optimizing parameters of support vector machine using fast messy genetic algorithm for dispute classification
TL;DR: This study proposes an optimized hybrid artificial intelligence model to integrate a fast messy genetic algorithm (fmGA) with a support vector machine (SVM) that achieves better cross-fold prediction accuracy compared to other baseline models and previous works.
Book ChapterDOI
A Hybrid GA-GSA Algorithm for Optimizing the Performance of an Industrial System by Utilizing Uncertain Data
TL;DR: This chapter presents a novel hybrid GA-GSA algorithm to permit the reliability analyst to increase the performance of the system by utilizing the uncertain data and maximizes the Reliability, Availability, and Maintainability parameters simultaneously for increasing the performance and productivity of theSystem.
Journal ArticleDOI
Multi-objective non-linear programming problem in intuitionistic fuzzy environment
TL;DR: Experimental results indicate that the proposed approach to solving multi-objective optimization problem under the optimistic and pessimistic view point may yield better solutions to these types of problems than those obtained by using current algorithms.
Journal ArticleDOI
Non-linear flexural and dynamic response of CNT reinforced laminated composite plates
TL;DR: In this paper, the non-linear flexural and dynamic response of CNT reinforced laminated composite plates using fast converging finite double Chebyshev polynomials is analyzed.
References
More filters
Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Journal ArticleDOI
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Proceedings ArticleDOI
A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Book
Fuzzy Set Theory - and Its Applications
TL;DR: The book updates the research agenda with chapters on possibility theory, fuzzy logic and approximate reasoning, expert systems, fuzzy control, fuzzy data analysis, decision making and fuzzy set models in operations research.