This study, for its research subjects, uses patients who had undergone total knee replacement surgery from the database of the National Health Insurance Administration. Through the review of literatures and the interviews with physicians, important factors are selected after careful screening. Then using Cross Entropy Method, Genetic Algorithm Logistic Regression, and Particle Swarm Optimizatio...

In this paper, we have considered a series-parallel system to find out optimum system reliability with an additional entropy objective function. Maximum system reliability of series-parallel system is depending on proper allocation of redundancy component in different stage. The goal of entropy based reliability redundancy allocation problem is to find optimal number of redundancy component in ...

We show that the entropy of a message can be tested in a device-independent way. Specifically, we consider a prepare-and-measure scenario with classical or quantum communication, and develop two different methods for placing lower bounds on the communication entropy, given observable data. The first method is based on the framework of causal inference networks. The second technique, based on co...

Cross Entropy has been recently applied to combinatorial optimization problems with promising results. This paper proposes a new cross-entropy based algorithm for monotonic integer programming problems with knapsack-type constraints. We show how the metaheuristic method can be adapted to tackle constrained problems, provided that some basic mathematical properties are enforced. Furthermore, som...

Clustering is an important unsupervised learning paradigm, but so far the traditional methodologies are mostly based on the minimization of the variance between the data and the cluster means. Here we propose a new evaluation function based on a recently developed information theoretic measure defined from Renyi’s entropy. We show how to apply Renyi’s entropy to clustering and analyze the resul...

Recently, different methods have been proposed for portfolio optimization and decision making on investment issues. This article aims to present a new method for portfolio formation based on Data Envelopment Analysis (DEA) and Entropy function. This new portfolio optimization method applies DEA in association with a model resulting from the insertion of the Entropy function directly into the op...

Support vector machine is an elegant tool for solving pattern recognition and regression problems. This paper presents a new smooth approach to solve support vector regression. Based on statistical learning theory and optimization theory, a smooth unconstrained optimization model for support vector regression is built with adjustable entropy technique. Newton descent method is used to solve the...

background: nowadays, analyzing human facial image has gained ever-increasing importance due to its various applications. image segmentation is required as a very important and fundamental operation for significant analysis and interpretation of images. methods: among the segmentation methods, image thresholding technique is one of the most well-known methods due to its simplicity, robustness a...

In this work, we propose a new approach of deriving the bounds between entropy and error from a joint distribution through an optimization means. The specific case study is given on binary classifications. Two basic types of classification errors are investigated, namely, the Bayesian and non-Bayesian errors. The consideration of non-Bayesian errors is due to the facts that most classifiers res...