For any agency dealing with the design of the water distribution network, an economic design will be an objective. In this research, Central Force Optimization (CFO) and Differential Evolution (DE) algorithm were used to optimize Ismail Abad water Distribution network. Optimization of the network has been evaluated by developing an optimization model based on CFO and DE algorithm in MATLAB and ...

While there is extensive literature on the prediction of corporate bankruptcies, little classification retail borrowers. This also true in Hungary. Recognising who at risk becoming a bad debtor not easy. There are several ways to analyse data, which may yield different results. In this paper, my aim predict default household loans using logistic regression and neural networks. The question is, ...

Problem statement: This study discusses the implementation of advanced logistic belief Neural Network for robot arms control. Approach: Given the desired trajectory of the end-effectors in space, the logistic function is used to compute the conditional probability of the neurons being active in response to its induced field. The computations of conditional probabilities are performed under two ...

An important challenge in machine learning is to find ways of learning quickly from very small amounts of training data. The only way to learn from small data samples is to constrain the learning process by exploiting background knowledge. In this report, we present a theoretical analysis on the use of constrained logistic regression for estimating conditional probability distribution in Bayesi...

This paper aims to study the construction and multivariate approximation of a class of network operators with logistic sigmoidal functions. First, a class of even and bell-shaped function with support on R is constructed by using appropriate translation and combination of the logistic function. Then, the constructed function is employed as activation function to construct a kind of so-called Ca...

Cox’s proportional hazard model or logistic regression model has been the classical mathematical approach to predict transplant results, but artificial neural networks may offer better results. In order to compare both methods, a logistic regression and a neural network model were generated to predict early transplant failure assessed at 90 days. Methods: Medical charts from 701 liver transplan...