In this study, we propose a novel method for medical problem, it is the integration of particle swarm optimization (PSO) and decision tree (C4.5) named PSO + C4.5 algorithm. To evaluate the effectiveness of PSO + C4.5 algorithm, it is implemented on 5 different data sets of life sciences obtained from UCI machine learning databases. Moreover, the results of PSO + C4.5 implementation are compare...

the analysis of flow in water-distribution networks with several pumps by the content model may be turned into a non-convex optimization uncertain problem with multiple solutions. newton-based methods such as gga are not able to capture a global optimum in these situations. on the other hand, evolutionary methods designed to use the population of individuals may find a global solution even for ...

in this paper, a new formula is applied for the calculation of gravity anomalies from a cylinder model representing a geological body. compared to conventional methods, this new development allows the cylinder to be freely oriented in space. 38 gravity forward models are produced each of which anomaly attributes are calculated. then a linear relationship is established between attributes and so...

Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search techniqu...

Support Vector Regression (SVR) is Support Vector Machine (SVM) is used for regression case. Regression method is one of prediction season method has been commonly used. SVR process requires kernel functions to transform the non-linear inputs into a high dimensional feature space. This research was conducted to predict rainfall in the dry season at 15 weather stations in Indramayu district. The...

Abstract: In this study an appropriate computational approach was presented for estimating the boiling temperatures of 41 different types of olefins and their derivatives. Based on the guidelines of this approach, several structural indices related to the organic components were applied using graph theory. Meanwhile, in addition to evaluating the relation between the boiling temperatures of ole...

In this paper, a novel distributed approach based on particle swarm optimization (PSO) has been proposed for distributed regression over sensor networks. Besides distributed data, the limitations of sensor nodes make doing regression more difficult. Conventional methods employ numerical optimization techniques such as gradient descent or Nelder-Mead Simplex algorithms in which the sensor nodes ...

background: disability is the most important determinants of disease course, treatment and rehabilitation outcomes and consequently the quality of life in patients with multiple sclerosis. the aim of the present study was to determine the relationship of disability and quality of life in multiple sclerosis patients.   methods: this cross-sectional study was performed on 325 patients referred to...

The Particle Swarm Optimization (PSO) technique was employed to optimize an industrial chemical process characterized by being difficult to be optimized by conventional methods. The chemical process is a three phase catalytic slurry reactor in which the reaction of the hydrogenation of o-cresol producing 2-methyl-cyclohexanol is carried out. The process was represented by a multivariable non-li...