Search results for "Optimization algorithm"

Determination of water speciation in hydrous haplogranitic glasses with partial Raman spectra

2020

Abstract We use a mathematical approach to decompose the Raman water band at 3000 cm−1 to 3750 cm−1 into two partial Raman spectra corresponding to the individual Raman activity of the two water species, i.e., molecular water (H2Om) and OH-groups, present in hydrous rhyolitic glasses. The approach is based on a least-squares optimization algorithm and the assumption that the water band can be expressed as a linear combination of two partial Raman spectra. Our model makes no assumptions regarding the shape of the partial Raman spectra. The model input consists of about 700 Raman spectra from hydrous haplogranitic (HPG8) compositions with total water contents from 0.6 to 3.1 wt% and with know…

Ant Colony Optimisation-Based Classification Using Two-Dimensional Polygons

2016

The application of Ant Colony Optimization to the field of classification has mostly been limited to hybrid approaches which attempt at boosting the performance of existing classifiers (such as Decision Trees and Support Vector Machines (SVM)) — often through guided feature reductions or parameter optimizations.

Algorithmic Approach for Slot Filling Factors Determination in Electrical Machines

2018

In several industrial sectors, such as electric and hybrid traction, the demand for increasingly efficient and high power density electrical machines has grown considerably over the last few years. The improvement of slot filling factor of the electrical machines is an useful provision to satisfy this request. In particular, this topic has been the subject of interest for the industrial sector in recent years, since the technology of winding processes have evolved and allow an economically sustainable realization of windings with an ordered structure rather than randomly. The winding phase must be supported by an accurate design process in which it is possible to evaluate the maximum slot f…

2019

Worries about possible harmful effects of new technologies (modern health worries) have intensely been investigated in the last decade. However, the comparability of translated self-report measures across countries is often problematic. This study aimed to overcome this problem by developing psychometrically sound brief versions of the widely used 25-item Modern Health Worries Scale (MHWS) suitable for multi-country use. Based on data of overall 5,176 individuals from four European countries (England, Germany, Hungary, Sweden), Ant Colony Optimization was used to identify the indicators that optimize model fit and measurement invariance across countries. Two scales were developed. A short (…

Methods matter: Testing competing models for designing short-scale Big-Five assessments

2015

Abstract Many psychological instruments are psychometrically inadequate because derived person-parameters are unfounded and models will be rejected using established psychometric criteria. One strategy towards improving the psychometric properties is to shorten instruments. We present and compare the following procedures for the abbreviation of self-report assessments on the Trait Self-Description Inventory in a sample of 14,347 participants: (a) Maximizing reliability/main loadings, (b) Minimizing modification indices/cross loadings, (c) the PURIFY Algorithm in Tetrad, (d) Ant Colony Optimization, and (e) a genetic algorithm. Ant Colony Optimization was superior to all other methods in imp…

An environment based approach for the ant colony convergence

2020

Abstract Ant colony optimization (ACO) algorithms are a bio inspired solutions which have been very successful in combinatorial problem solving, also known as NP-hard problems, including transportation system optimization. As opposed to exact methods, which could give the best results of a tested problem, this meta-heuristics is based on the stochastic logic but not on theoretical mathematics demonstration (or only on certain well defined applications). According to this, the weak point of this meta-heuristics is his convergence, its termination condition. We can finds many different termination criteria in the scientific literature, yet most of them are costly in resources and unsuitable f…

Synthetic Genes for artificial ants. Diversity in ant colony optimization algorithms

2010

Inspired from the fact that the real world ants from within a colony are not clones (although they may look alike, they are different from one another), in this paper, the authors are presenting an adapted ant colony optimisation (ACO) algorithm that incorporates methods and ideas from genetic algorithms (GA). Following the first (introductory) section of the paper is presented the history and the state of the art, beginning with the stigmergy and genetic concepts and ending with the latest ACO algorithm variants as multiagent systems (MAS). The rationale and the approach sections are aiming at presenting the problems with current stigmergy-based algorithms and at proposing a (possible - ye…

Cryptanalysis of Knapsack Cipher Using Ant Colony Optimization

2018

Ant Colony Optimization is a search metaheuristic inspired by the behavior of real ant colonies and shown their effectiveness, robustness to solve a wide variety of complex problems. In this paper, we present a novel Ant Colony Optimization (ACO) based attack for cryptanalysis of knapsack cipher algorithm. A Cipher-text only attack is used to discover the plaintext from the cipher-text. Moreover, our approach allows us to break knapsack cryptosystem in a minimum search space when compared with other techniques. Experimental results prove that ACO can be used as an effective tool to attack knapsack cipher.

Feature selection with Ant Colony Optimization and its applications for pattern recognition in space imagery

2016

This paper presents a feature selection (FS) algorithm using Ant Colony Optimization (ACO). It is inspired by the particular behavior of real ants, namely by the fact that they are capable of finding the shortest path between a food source and the nest. There are considered two ACO-FS model applications for pattern recognition in remote sensing imagery: ACO Band Selection (ACO-BS) and ACO Training Label Purification (ACO-TLP). The ACO-BS reduces dimensionality of an input multispectral image data by selecting the “best” subset of bands to accomplish the classification task. The ACO-TLP selects the most informative training samples from a given set of labeled vectors in order to optimize the…

Partial Discharges analysis and parameters identification by continuous Ant Colony Optimization

2008

The technique of ant colony optimization has been employed in this paper to efficiently deal with the problem of parameters identification in partial discharge, PD, analysis. The latter is a continuous optimization problem. From the technical point of view the identification of these parameters allows the modeling of the phenomenon of Partial Discharges in dielectrics. In this way it is possible the early diagnosis of defects in Medium Voltage cable lines and components and thus it is possible to prevent possible outages and service interruptions. Analytically, the problem consists of finding the Weibull parameters of the Pulse Amplitude Distribution (PAD) distributions allowing the identif…