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THE POTENTIAL OF genetic algorithmS FOR CONCEPTUAL DESIGN OF ROTOR SYSTEMS

ENGINEERING OPTIMIZATION 1995年第3期24卷 221-238页

作者： CROSSLEY, WA WELLS, VL LAANANEN, DH [a] Department of Mechanical and Aerospace Engineering Arizona State Uniuersity Tempe Arizona U.S.A.

The capabilities of the genetic algorithm as a non-calculus based, global search method makes it potentially useful in the conceptual design of rotor systems. Coupling reasonably simple analysis tools to the genetic algorithm was accomplished, and the resulting program was used to generate designs for rotor systems to match requirements similar to those of both an existing helicopter and a proposed helicopter design. This provides a comparison with the existing design and also provides insight into the potential of genetic algorithms in design of new rotors.

关键词： HELICOPTER ROTOR DESIGN HELICOPTER ROTOR OPTIMIZATION genetic algorithm application

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Intelligent Technologies Integration in the Task of Unaccented Trajectories Search in Robotics

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IFAC-PapersOnLine 2018年第30期51卷 538-543页

作者： Shakhmametova, Gouzel R. Yusupova, Nafisa I. Computer Science and Robotics Department Ufa State Aviation Technical University Ufa Russia

The problem of search for multilink manipulators trajectories in complex environment with obstacles, taking into consideration the initial point and the manipulator length is presented in the article. The main approach based on the genetic algorithm application is offered for the unaccented trajectories search problem solution. For increase in overall performance of the basic algorithm, intelligent technologies integration in the form of genetic algorithm and technology of expert systems hybridization is offered. Analysis of the experimental data showed that the average percent of points achievement is 70-85%. The methods and algorithms of trajectories search suggested in the article may be used for different types of environments with obstacles. © 2016

关键词： Trajectories applications Expert systems genetic algorithms Intelligent systems Manipulators Robotics Complex environments genetic algorithm application Handling device Initial point Intelligent technology Multi link Search problem

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Dynamic power minimization during combinational circuit testing as a traveling salesman problem

Dynamic power minimization during combinational circuit test...

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IEEE Congress on Evolutionary Computation

作者： Sokolov, A Sanyal, A Whitley, D Malaiya, Y Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

ISBN: (纸本)0780393635

Testing of VLSI circuits can cause generation of excessive heat which can damage the chips under test. In the random testing environment, high-performance CMOS circuits consume significant dynamic power during testing because of enhanced switching activity in the internal nodes. Our work focuses on the fact that power minimization is a Traveling Salesman Problem (TSP). We explore application of local search and genetic algorithms to test set reordering and perform a quantitative comparison to previously used deterministic techniques. We also consider reduction of the original test set as a dual-objective optimization problem, where switching activity and fault coverage are the two objective functions.

关键词： combinational circuit testing test vector automatic test pattern generator (ATPG) fault coverage traveling salesman problem (TSP) genetic algorithm application weight-biased edge crossover multi-objective genetic algorithm

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Development of a Cost Oriented Grinding Strategy and Prediction of Post Grind Roughness using Improved Grinder Models

Development of a Cost Oriented Grinding Strategy and Predict...

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作者： Sriram Srinivasan Virginia Polytechnic Institute and State University

学位级别：硕士

Irregularities in pavement profiles that exceed standard thresholds are usually rectified using a Diamond Grinding Process. Diamond Grinding is a method of Concrete Pavement Rehabilitation that involves the use of grinding wheels mounted on a machine that scraps off the top surface of the pavement to smooth irregularities. Profile Analysis Software like ProVAL© offers simulation modules that allow users to investigate various grinding strategies and prepare a corrective action plan for the pavement. The major drawback with the current Smoothness Assurance Module© (SAM) in ProVAL© is that it provides numerous grind locations which are both redundant and not feasible in the field. This problem can be overcome by providing a constrained grinding model in which a cost function is minimized; the resulting grinding strategy satisfies requirements at the least possible cost. Another drawback with SAM exists in the built-in grinder models that do not factor in the effect of speed and depth of cut on the grinding head. High speeds or deep cuts will result in the grinding head riding out the cut and likely worsening the roughness. A constrained grinding strategy algorithm with grinder models that factor in speed and depth of cut that results in cost effective grinding with better prediction of post grind surfaces through simulation is developed in this work. The outcome of the developed algorithm is compared to ProVAL's© SAM results.

关键词： Pavement Profiles Diamond Grinding Pavement Rehabilitation Grinding Strategy genetic algorithm application

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Development of a Cost Oriented Grinding Strategy and Prediction of Post Grind Roughness using Improved Grinder Models

Development of a Cost Oriented Grinding Strategy and Predict...

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作者： Srinivasan, Sriram Virginia Tech | University

关键词： Pavement Profiles Diamond Grinding Pavement Rehabilitation Grinding Strategy genetic algorithm application Thesis

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A novel multi-objective medical feature selection compass method for binary classification

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ARTIFICIAL INTELLIGENCE IN MEDICINE 2022年 127卷 102277-102277页

作者： Gutowski, Nicolas Schang, Daniel Camp, Olivier Abraham, Pierre Univ Angers LERIA F-49000 Angers France ESEO TECH ERIS 10 Blvd Jean Jeanneteau F-49100 Angers France Univ Hosp Angers Exercise & Sports Med 4 Rue Larrey F-49100 Angers France Univ Angers INSERM 1083 CNRS 6015 40 Rue RennesBP 73532 F-49035 Angers 01 France

The use of Artificial Intelligence in medical decision support systems has been widely studied. Since a medical decision is frequently the result of a multi-objective optimization problem, a popular challenge combining Artificial Intelligence and Medicine is Multi-Objective Feature Selection (MOFS). This article proposes a novel approach for MOFS applied to medical binary classification. It is built upon a genetic algorithm and a 3 -Dimensional Compass that aims at guiding the search towards a desired trade-off between: Number of features, Accuracy and Area Under the ROC Curve (AUC). This method, the genetic algorithm with multi-objective Compass (GAwC), outperforms all other competitive genetic algorithm-based MOFS approaches on several real-world medical datasets. Moreover, by considering AUC as one of the objectives, GAwC guarantees the classification quality of the solution it provides thus making it a particularly interesting approach for medical problems where both healthy and ill patients should be accurately detected. Finally, GAwC is applied to a real-world medical classification problem and its results are discussed and justified both from a medical point of view and in terms of classification quality.

关键词： genetic algorithm application Multi-objective feature selection Extreme learning machine Machine learning Cardiology Medicine

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Design of Heat Conduction Panel: The Case of Multiple Heating Elements Cooled by a Displaced Heat Sink (Reprinted from Thermal Issues in Emerging Technologies: Theory and application, January, 2007)

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JOURNAL OF ELECTRONIC PACKAGING 2008年第4期130卷 41108-41108页

作者： Nakayama, Wataru Therm Tech Int Oh Iso Kanagawa 2550004 Japan

This paper reports the design study performed on a heat conduction panel having several heat sources at separate locations and a heat sink on one of the panel corners. The panel is given a thickness distribution so as to provide spatially varying heat conduction paths from the heat sources to the heat sink. The objective of thickness distribution design is to reduce the variation among heat source temperatures and the maximum heat source temperature simultaneously. The genetic algorithm is used to search for an optimum thickness distribution. The problem is a generic representation of the situations that are becoming common in a compact electronic equipment. [DOI: 10.1115/1.2993137]

关键词： heat conduction path design multiple heat sources displaced heat sink genetic algorithm application

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