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Article | 27-August-2018

OPTIMIZATION OF TRUSSES WITH SELF-ADAPTIVE APPROACH IN GENETIC ALGORITHMS

This paper presents a genetic algorithm method for the optimization of the weight of steel truss structures. In the method of genetic algorithm integer encoding of a discrete set of design variables and novel self-adaptive method based on fuzzy logic mechanism are applied for improving the quality and speed of optimization. Self-adaptive method is applied simultaneously in the selection of chromosomes and to control basic parameters of genetic algorithm. The algorithm proposed in the work was

Krzysztof GRYGIEREK

Architecture, Civil Engineering, Environment, Volume 9 , ISSUE 4, 67–78

Research Article | 13-December-2017

INVESTIGATION OF ADVANCED DATA PROCESSING TECHNIQUE IN MAGNETIC ANOMALY DETECTION SYSTEMS

Advanced methods of data processing in magnetic anomaly detection (MAD) systems are investigated. Raw signals of MAD based on component magnetic sensors are transformed into energy signals in the space of specially constructed orthonormalized functions. This procedure provides a considerable improvement of the SNR thus enabling reliable target detection. Estimation of the target parameters is implemented with the help of Genetic Algorithm. Numerous computer simulations show good algorithm

B. Ginzburg, L. Frumkis, B.Z. Kaplan, A. Sheinker, N. Salomonski

International Journal on Smart Sensing and Intelligent Systems, Volume 1 , ISSUE 1, 110–122

Research Article | 13-December-2017

AUTOMATIC ADJUSTMENT FOR LASER SYSTEMS USING A STOCHASTIC BINARY SEARCH ALGORITHM
TO COPE WITH NOISY SENSING DATA

(2) adjustment precision due to observational noise. In order to solve these problems, we propose a robust and efficient automatic adjustment method for the optical axes of laser systems using a binary search algorithm. Adjustment experiments for optical axes with 4-DOF demonstrate that the adjustment time could be reduced to half the conventional adjustment time with the genetic algorithm. Adjustment precision was enhanced by 60%.

Hirokazu Nosato, Nobuharu Murata, Tatsumi Furuya, Masahiro Murakawa

International Journal on Smart Sensing and Intelligent Systems, Volume 1 , ISSUE 2, 512–533

Article | 28-August-2018

OPTIMIZATION OF WINDOW SIZE DESIGN FOR DETACHED HOUSE USING TRNSYS SIMULATIONS AND GENETIC ALGORITHM

building orientation has been analysed. Optimal selection of these parameters for reduction of the energy consumption has been carried out. Genetic algorithms were used for the optimization, while TRNSYS program was used for energy analysis. The analyses were performed on an exemplary single family detached house. Self-adaptive genetic algorithm connected with energy building simulation successfully identifies the lowest energy costs. Optimal window type and size design and window orientation reduce

Joanna FERDYN-GRYGIEREK, Krzysztof GRYGIEREK

Architecture, Civil Engineering, Environment, Volume 10 , ISSUE 4, 133–140

Research paper | 10-April-2013

Labeling of Human Motion Based on CBGA and Probabilistic Model

In this paper, we present a novel method for the labeling of human motion which uses Constraint-Based Genetic Algorithm (CBGA) to optimize the probabilistic model of body features and construct the set of conditional independence relations among the body features by a fitness function. The approach also allows the user to add custom rules to produce valid candidate solutions to achieve more accurate results with constraint-based genetic operators. Specifically, we design the fitness function

Fuyuan Hu, Hau San Wong

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 2, 583–609

Article | 06-November-2017

MODELING AND CONTROL OF BALL AND BEAM SYSTEM USING MODEL BASED AND NON-MODEL BASED CONTROL APPROACHES

The ball and beam system is a laboratory equipment with high nonlinearity in its dynamics. The aims of this research are to model the ball and beam system considering nonlinear factors and coupling effect and to design controllers to control the ball position. The LQR is designed considering two Degrees-of-Freedom and coupling dynamics. The parameters of the LQR are tuned using Genetic Algorithm (GA). Jacobian linearization method is used to linearize the system around operating-point. Due to

Mohammad Keshmiri, Ali Fellah Jahromi, Abolfazl Mohebbi, Mohammad Hadi Amoozgar, Wen-Fang Xie

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 1, 14–35

Research Article | 01-December-2011

BOTTOM-UP APPROACH FOR BEHAVIOR ACQUISITION OF AGENTS EQUIPPED WITH MULTI-SENSORS

While the top-down approach of artificial intelligence encounters the frame problem, the bottom-up approach based on a creature’s evolution and behavior is effective for robotic design of intellectual behavior in a specific field. We propose the Evolutionary Behavior Table System (EBTS) using a simple genetic algorithm (SGA) to acquire the autonomous cooperative behavior of multi-agents as the bottom-up approach. In EBTS, a set of rules is expressed as a table composed of sensor input columns

Naoto Hoshikawa, Masahiro Ohka, Hanafiah Bin Yussof

International Journal on Smart Sensing and Intelligent Systems, Volume 4 , ISSUE 4, 583–606

Research Article | 13-December-2017

TWO METHODOLOGIES TOWARD ARTIFICIAL TACTILE AFFORDANCE SYSTEM IN ROBOTICS

, we treat a long string composed of rule strings as a gene to obtain an optimum gene that adapts to its environment using a genetic algorithm (GA). For methodology 1, we established an ATAS composed of 3 to 5 modules to accomplish such tasks as object grasping, pick and place, cap screwing, and assembling. Using methodology 1, a two-hand-arm robot equipped with an optical threeaxis tactile sensor performed the above tasks. For methodology 2, we propose the Evolutionary Behavior Table System (EBTS

M. Ohka, N. Hoshikawa, J. Wada, H. B. Yussof

International Journal on Smart Sensing and Intelligent Systems, Volume 3 , ISSUE 3, 466–487

Research Article | 20-November-2017

STACKED REGRESSION WITH A GENERALIZATION OF THE MOORE-PENROSE PSEUDOINVERSE

Tomasz Górecki, Maciej Łuczak

Statistics in Transition New Series, Volume 18 , ISSUE 3, 443–458

Research Article | 27-December-2017

The Design and Evaluation of a Strategy of Data Placement in Cloud Computing Platform

Wei Guo, Kaibo Luo, Xinjun Wang, Lizhen Cui

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 1, 13–30

Research Article | 12-December-2017

MICRO-GENERATOR DESIGN FOR SMART GRID SYSTEM (COMPARATIVE STUDY)

problem formulation. Then a genetic algorithm is formulated for obtaining maximum efficiency and minimizing machine size. In the second genetic problem formulation, we attempt to obtain minimum mass, the machine sizing that is constrained by the non-linear constraint function of machine losses. Finally, an optimum torque per ampere genetic sizing is predicted. All results are simulated with MATLAB, Optimization Toolbox and its Genetic Algorithm. Finally, six design examples comparisons are introduced

Adel El Shahat, Ali Keyhani, Hamed El Shewy

International Journal on Smart Sensing and Intelligent Systems, Volume 3 , ISSUE 2, 176–216

Research Article | 27-December-2017

PARETO OPTIMAL ROBUST FEEDBACK LINEARIZATION CONTROL OF A NONLINEAR SYSTEM WITH PARAMETRIC UNCERTAINTIES

The problem of multi-objective robust feedback linearization controller design of nonlinear system with parametric uncertainties is solved in this paper. The main objective of this paper is to propose an optimal technique to design a robust feedback linearization controller with multi-objective genetic algorithm. A nonlinear system is considered as a benchmark and feedback linearization controller is designed for deterministic and probabilistic model of the benchmark. Three and four conflicting

A. Hajiloo, M. samadi, N. Nariman-Zadeh

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 1, 214–237

Review | 06-August-2019

MULTI-VARIABLE OPTIMIZATION MODELS FOR BUILDING ENVELOPE DESIGN USING ENERGYPLUS SIMULATION AND METAHEURISTIC ALGORITHMS

genetic algorithm method to select the best combination of several components of the building envelope (orientation, wall, roof and foundation insulation, window area, glazing type, air leakage level and thermal mass). In turn Bichiou and Krarti [28] compared the performance of three optimization techniques (genetic algorithm, particle swarm optimization, and sequential search methodology) to select HVAC system design features and its operation settings. To perform the optimization analysis the

Krzysztof GRYGIEREK, Joanna FERDYN-GRYGIEREK

Architecture, Civil Engineering, Environment, Volume 12 , ISSUE 2, 81–90

Article | 11-April-2018

Research on Combination Forecasting Model of Mine Gas Emission

This paper focuses on the effective analysis of the mine gas emission monitoring data, so as to realize the accurate and reliable mine gas emission prediction. Firstly, a weighted multiple computing models based on parametric t– norm is constructed. And a new mine gas emission combination forecasting method is proposed. The BP neural network model and the support vector machine were used as the single prediction models. Finally, genetic algorithm and least square method were used to

Liang Rong, Chang Xintan, Jia Pengtao, Dong Dingwen

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 194–198

Article | 01-December-2014

RESEARCH OF MULTI SENSOR INTELLIGENT SYSTEM SIGNAL FUSION AND RECONSTRUCTION

This paper studies some key technology of multifunctional sensor signal reconstruction. The multifunctional sensor signal reconstruction problem, presented a multifunctional sensor signal reconstruction method based on B spline and the extended Calman filter. The method of inverse model of the process was studied, gives a method to estimate signal reconstruction accuracy and computation. Genetic algorithm is proposed to balance the multifunctional sensor signal reconstruction accuracy and

Junjie Yang, Wenxiang Chen, Zhihe Fu, Wei Wu, Zhiping Xie

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 4, 1701–1716

Article | 10-April-2018

Association Rule Mining Based on Estimation of Distribution Algorithm for Blood Indices

To come over the limitations of Apriori algorithm and association rule mining algorithm based on Genetic Algorithm (GA), this paper proposed a new association rule mining algorithm based on the population-based incremental algorithm (PBIL), which is a kind of distribution estimation algorithms. The proposed association rule-mining algorithm keeps the advantages of GA mining association rules in coding and the fitness function. Through using probability vector possessing learning properties to

Xinyu Zhang, Botu Xue, Guanghu Sui, Jianjiang Cui

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 20–26

Article | 11-June-2016

AN IMPROVED MULTI-OBJECTIVE EVOLUTIONARY OPTIMIZATION ALGORITHM FOR SUGAR CANE CRYSTALLIZATION

. Therefore, this paper puts forward a different multi-objective framework, and correspondingly, an improved optimization algorithm is applied to intermittent sugar cane crystallization. This method combines the elitist non-dominated sorting genetic algorithm (NSGA-II) with technique for order preference which is similar to an ideal solution (TOPSIS), and it provides a quantitative way to analyze the effect of both seed characteristics and process variables on the trade-off between MA and CV. Furthermore

Yanmei Meng, Wenxing Li, Qingwei Chen, Xian Yu, Kangyuan Zheng, Guancheng Lu

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 953–978

Article | 09-April-2018

Multi Objective Optimization of Virtual Machine Migration Placement Based on Cloud Computing

experiments are carried out and the conclusions are made for it. The algorithm can obtain the optimal solution through the continuous updating of pheromone. The main consideration is the Service level contract violation rate(S), Resource loss(W),Power consumption (P). Experimental results show that ,compared with the traditional heuristic method and genetic algorithm, the algorithm is advantageous to the parallel computation, and it’s able to achieve the optimal tradeoff and compromise between

Sun Hong, Tang Qing, Xu Liping, Chen Shiping

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 2, 120–129

Research Article | 01-September-2017

HYBRID DATA APPROACH FOR SELECTING EFFECTIVE TEST CASES DURING THE REGRESSION TESTING

concerns for effective testing as well as cost of the testing process. During the Regression testing, executing all the test cases from existing test suite is not possible because that takes more time to test the modified software. This paper proposes new Hybrid approach that consists of modified Greedy approach for handling the test case selection and Genetic Algorithm uses effective parameter like Initial Population, Fitness Value, Test Case Combination, Test Case Crossover and Test Case Mutation for

M. Mohan, Tarun Shrimali

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 5, 1–24

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