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Cluster is bunch of similar items. Unsupervised classification of patterns into clusters is known as clustering. It is useful in knowledge discovery in data. Clustering is able to deal with different data types. Fuzzy rules are used for data intelligence illustration purpose. User gets highly interpretable discovered clusters using fuzzy rules. To generate accurate fuzzy rules triangular membership...
Nuclear power plant is a large and complex system, when it fail, a fast and accurate fault diagnosis is needed to ensure a safe and efficient working of nuclear power plant. In this paper, the feasibility of exploiting fault diagnosis system based on fuzzy sets theory in nuclear plant was demonstrated. The genetic algorithm was introduced to optimize the rules of diagnosis, so as to achieve fast fault...
Controlling the loop flow phenomena is very important issue in the de-regulated power systems. It should be solved very efficiently. We have formulated the loop flow problem in fuzzy environment, as a multi-objective function using fuzzy set theory and fuzzy decision making. Then the resulted single objected optimization problem is solved using differential evolution which is one of the evolutionary...
As one of the triple constraint of project management, project completion time is very important issue. This is considerable for wide range of projects, especially for the time-terminated ones. Beside standard network planning methods, such as CPM, PERT, PDM etc. there are variety of alternative methods, based on previous ones, which are used in order to obtain even better project duration evaluations...
In Multi-Criteria Decision Making (MCDM), decisions are based on several criteria that are usually conflicting and non-homogenously satisfied. Non-additive (fuzzy) measures along with the Choquet integral can model and aggregate the levels of satisfaction of these criteria by considering their relationships. However, in practice, it is difficult to identify such fuzzy measures. An automated process...
This paper addresses the shortest path problem in a fuzzy directed graph. Unlike the previous approaches, the proposed approach can be applied for networks which may consist of cycles and parallel arcs that each arc length is defined by a fuzzy number. It should be noted that the crisp shortest path problem has already been solved however in many real world applications the exact value of arcs is...
This paper studies the job-shop scheduling problems of multi-process routes with fuzzy processing time and fuzzy due date, and establishes a fuzzy scheduling model to reach the optimization goals of maximum average satisfaction index. Then a co-evolutionary algorithm combined with genetic algorithm and discrete particle swarm optimization algorithm is presented, which improves the chromosome encoding...
In view of the coal plow of the load and energy consumption question, optimized the cutting and parameter movement for plow body of on improved genetic algorithm multi-objective optimization strategy. The optimized results indicate that the cutting consumption reduces 16.96%, productivity capability rises 23.38%, loading area uniformity rises 16.62%, productivity capability of coal plow obtains obviously...
The secondary structure prediction of RNAs is an important classical problem in bioinformatics. The standard solution is to predict the secondary structure possessing the minimum free energy. In this paper, we propose a fuzzy adaptive particle swarm optimization (FPSO) combining particle swarm optimization (PSO) and fuzzy logic control (FLC) to predict RNA secondary structure with the minimum energy...
Accurate fingerprint recognition system is the problem encountered in the field of biometric identification. Use of back propagation network for recognition problems resulted in inconsistent and unpredictable performance. The proposed approach using soft computing tools like Fuzzy, Neural and Genetic overcomes low recognition rate, low accuracy and increased time of recovery. The stages of this approach...
This paper presented a genetic - fuzzy logic based Proportional-Integral-Derivative controller (GFPID) for automatic generation control of two area thermal-thermal power system. Genetic algorithm has been applied to simultaneously tune PID gains, membership functions and control rules of FPID controller to minimize the frequency deviations of the system against the load disturbances. An objective...
Internet e-mails have become a common medium of communication for nearly every one. With the fast growing, spam interferes with valid email, and bothers users. This paper proposes a new fuzzy adaptive multi-population genetic algorithm (FAMGA), in order to automatically find the best feature subset to classify spam e-mails. FAMGA consists of multiple subpopulations, and each population runs independently...
The software of auto-tuning parameters of PID control is developed for industrial controller. The output response curve of control system is recognized, and the scopes of the controller parameters are given to meet expected control index by fuzzy tuning rules based on pattern recognition. The PID parameters are optimized by means of genetic algorithm based on the optimization function of over-shoot,...
Since 1960, the pavement serviceability index has supported the efforts of engineers who make decisions concerning maintenance strategies. The data of pavement surfaces do not belong to a normal distribution. Because the data violate the basic assumptions of linear regression, the pavement serviceability index is not suitable for regression modeling. Many kinds of prediction models with non-statistical...
This paper describes a hybrid meta-heuristic for combinatorial optimization problems with specific reference to the travelling salesman problem (TSP). The method is a combination of genetic algorithms (GA) and greedy randomized adaptive search procedures (GRASP). A new adaptive fuzzy greedy search operator is developed for this hybrid method. Computational experiments using a wide range of standard...
In this study, the genetic algorithms and fuzzy comprehensive evaluation were used together to analyze the product assessment data. It is explored which operators were employed and whether everybody used the same operators in fuzzy comprehensive evaluation. It investigated the evaluation made by undergraduates on Master Kong beef instant noodle. The results demonstrated that males used the “max...
When an organization utilizes modern technology in its manufacturing process, it needs to update and upgrade its facilities repetitively by efficient ways to stay with great productivity along with efficiency so. Capital Budgeting (CB) problem is one of the most important issues in decision makings about capital in the manufacturing management. Sometimes all variables and parameters are not necessarily...
Fuzzy Logic Controllers (FLCS) are rule-based system that successfully incorporate the flexibility of human-decision making by means of the use of fuzzy set theory. This paper provides an overview on evolutionary learning methods for the automated design and optimization of fuzzy logic controllers. A three-stage evolution framework that uses Genetic Programming (GP) and Genetic Algorithms (GAS) evolves...
The Fuzzy-Go search engine develops a fuzzy ontology to capture the similarities of terms in the ontology for accomplishing the semantic search of keywords, a web crawler to gather and classify web pages, and a fuzzy search mechanism to aggregate all fuzzy factors based on their degrees of importance and degrees of satisfaction. In this paper, we apply the genetic algorithm to propose a self-adaptation...
Using the superiority of the genetic algorithms solving nonlinear problems which is applied to feature extraction on Text Categorization is proposed in this paper. A synonym problem in text is fully considered by this method during the feature extraction processing, and is processed using the concept of fuzzy set. The membership of synonymous as the fitness function of Genetic Algorithm is carried...
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