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The estimation of software effort is an essential and crucial activity for the software development life cycle. Software effort estimation is a challenge that often appears on the project of making a software. A poor estimate will produce result in a worse project management. Various software cost estimation model has been introduced to resolve this problem. Constructive Cost Model II (COCOMO II Model)...
This paper describes the optimization of a linear discrete time controller and nonlinear fuzzy controller for a cylindrical tank located horizontally. The tank model is characterized by several non-linear behaviors like single positive action of the actuator, nonlinear relationship between the height and the inflow and saturation of the actuator given by the maximum flow. The results show a suitable...
One of the main challenges in addressing Non-Functional Requirements (NFRs) in designing systems is to take into account their interdependencies and mutual impacts. For this reason, they cannot be considered in isolation and a careful balance and tradeoff among them should be established. This makes it a difficult task to select design decisions and features that lead to the satisfaction of all different...
This paper introduces a theoretical new approach for training the adaptive-network-based fuzzy inference system (ANFIS) using Tree Physiology Optimization (TPO). The TPO is a heuristic method based on tree physiology. The method will be applied to nonlinear dynamic system.
In this paper we propose a new Gravitational Search Algorithm (GSA) using fuzzy logic to change alpha parameter and give a different gravitation and acceleration to each agent in order to improve its performance, we use this new approach for mathematical functions and present a comparison with original approach.
This study investigates the use of Genetic Algorithms (GA) to the design and implementation of Fuzzy Logic (FLC) for weigh-feeder control. A fuzzy logic is fully defined by its membership function (MF). What is the best to determine the membership function is the first question that has been tackled. Thus it is important to select the accurate membership functions but these methods possess one common...
The study of multi-objective optimization has matured to a level where uncertainty is considered when comparing and evaluating solutions for any given problem. This paper reviews the current techniques that have been proposed to include uncertainty within a multi-objective framework. Probabilistic as well as fuzzy methods are reviewed. A new method to identify sample representative solutions from...
Due to the unique characteristics such as handling complex, nonlinear, and sometimes intangible dynamic systems, fuzzy systems are used in the modeling of input-output data of the process. In this paper clustering algorithm is implemented in the design of a fuzzy logic controller (FLC) and for the determination of the optimal values of clustering parameters such as weighting exponent and the number...
Learning fuzzy rule-based systems with genetic algorithms can lead to very useful descriptions of several optimization and search problems. In the fuzzy logic method, when the inputs to the fuzzy controller in any process are increased, then the number of rules increases exponentially. To overcome the above problem, genetic algorithm (GA) is used. Genetic algorithm is a search and optimization technique...
This paper introduces a new hybrid approach for training the adaptive network based fuzzy inference system (ANFIS).This approach based on multi objective optimization mechanism for training parameters in antecedent part. It considers two cost functions as the objectives which are the maximum difference measurements between the real nonlinear system and the nonlinear model, and training mean square...
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