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THE CONTROLLED random search algorithm IN OPTIMIZING REGRESSION-MODELS

COMPUTATIONAL STATISTICS & DATA ANALYSIS 1995年第2期20卷 229-234页

作者： KRIVY, I TVRDIK, J UNIV OSTRAVA CS-70103 OSTRAVACZECH REPUBLIC

This paper deals with the problems of controlled random search algorithms (CRS algorithms) and their use in regression analysis. A modified CRS algorithm of Price is described, which is more effective when compared with the original algorithm in optimizing regression models, first non-linear ones. The principal modification consists in randomizing the search for the next trial points. Some results of testing the algorithm, using both real and modeled data, are given to illustrate its possibilities when estimating the parameters of non-linear regression models.

关键词： random search algorithm NONLINEAR REGRESSION MODELS

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An Intelligent Learning System Based on random search algorithm and Optimized random Forest Model for Improved Heart Disease Detection

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IEEE ACCESS 2019年 7卷 180235-180243页

作者： Javeed, Ashir Zhou, Shijie Liao Yongjian Qasim, Iqbal Noor, Adeeb Nour, Redhwan Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu 611731 Peoples R China Univ Sci & Technol Bannu Dept Comp Sci Bannu 28100 Pakistan King Abdulaziz Univ Fac Comp & Informat Technol Dept Informat Technol Jeddah 80221 Saudi Arabia Taibah Univ Dept Comp Sci Medina 42353 Saudi Arabia

Heart failure is considered one of the leading cause of death around the world. The diagnosis of heart failure is a challenging task especially in under-developed and developing countries where there is a paucity of human experts and equipments. Hence, different researchers have developed different intelligent systems for automated detection of heart failure. However, most of these methods are facing the problem of overfitting i.e. the recently proposed methods improved heart failure detection accuracy on testing data while compromising heart failure detection accuracy on training data. Consequently, the constructed models overfit to the testing data. In order, to come up with an intelligent system that would show good performance on both training and testing data, in this paper we develop a novel diagnostic system. The proposed diagnostic system uses random search algorithm (RSA) for features selection and random forest model for heart failure prediction. The proposed diagnostic system is optimized using grid search algorithm. Two types of experiments are performed to evaluate the precision of the proposed method. In the first experiment, only random forest model is developed while in the second experiment the proposed RSA based random forest model is developed. Experiments are performed using an online heart failure database namely Cleveland dataset. The proposed method is efficient and less complex than conventional random forest model as it produces 3.3% higher accuracy than conventional random forest model while using only 7 features. Moreover, the proposed method shows better performance than five other state of the art machine learning models. In addition, the proposed method achieved classification accuracy of 93.33% while improving the training accuracy as well. Finally, the proposed method shows better performance than eleven recently proposed methods for heart failure detection.

关键词： Heart failure hyperparameters optimization feature selection random search algorithm grid search algorithm

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random search algorithms for redundancy allocation problem of a queuing system with maintenance considerations

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2019年 185卷 144-162页

作者： Sabri-Laghaie, Kamyar Karimi-Nasab, Mehdi Urmia Univ Technol Fac Ind Engn Orumiyeh Iran Univ Hamburg Inst Operat Res Hamburg Germany

The Redundancy Allocation Problem (RAP) is becoming all the time more important in system reliability design. Therefore, RAP has been studied vastly for different systems and under various assumptions. One of the important systems that RAP can be applied to them is queuing systems. In many applications, reliability of queuing systems need to be improved with regard to some queuing and reliability cost constraints. Despite the importance of queuing systems in real world situations, RAP of these systems have not gained attention in the literature. Therefore, RAP of a queuing system with maintenance considerations and including queueing costs in the modeling of RAP is considered in this paper. To find optimal solutions of the problem, four random search algorithms are developed and compared based on the problem structures. According to the experiments, for unimodal solution spaces algorithms 1 and 2 and for multimodal solution spaces algorithms 3 and 4 are recommended.

关键词： Queuing system Redundancy Allocation Problem (RAP) Standby server Reliability analysis Repairman random search algorithm

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A region based random multi-pixel search algorithm to improve the binary hologram reconstruction quality

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OPTICS AND LASERS IN ENGINEERING 2023年 161卷

作者： Lu, Changgui Jin, Shuping Hu, Xuefang Zhao, Xiangyue Qi, Zhengqing Chen, Weidong Cui, Yiping Southeast Univ Adv Photon Ctr Nanjing 210096 Peoples R China Jinling Inst Technol Sch Network & Commun Engn Nanjing 211169 Peoples R China Southeast Univ Sch Elect Sci & Engn Nanjing Jiangsu Peoples R China

Direct binary search (DBS) is an effective method for the generation of binary computer-generated holograms (CGHs), which has been widely used in wavefront synthesis, optical tweezers and 3D display. However, the correlation of pixels in holograms is neglected in DBS, resulting the algorithm easily converging to local minimum and leading to an unsatisfactory reconstruction quality. To ameliorate this disadvantage, we proposed a new algorithm by randomly selecting multiple related pixels in the same region to generate hologram. Compared with DBS, the mean square error (MSE) of reconstructed image in simulation has declined from 844.85 to 445.74, the peak signal to noise ratio (PSNR) has increased from 18.86 to 21.64 and structural similarity (SSIM) has increased from 0.336 to 0.459. The reconstructed image in experiment shows fewer noise points and clearer outline. Both the numerical and experimental results demonstrate that the reconstruction quality can be improved by this algorithm, which will exhibit great applications in the fields of data storage, microscopy, and true sense dynamic 3D display.

关键词： Holography Binary hologram random search algorithm Direct binary search

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Incorporating Filters in random search algorithms for the Hourly Operation of a Multireservoir System

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2018年第2期144卷 04017088-04017088页

作者： Chen, Duan Leon, Arturo S. Fuentes, Claudio Gibson, Nathan L. Qin, Hui Sci Res Inst Changjiang River Dept Project Planning 23 Huangpu Rd Wuhan 430010 Hubei Peoples R China Univ Houston Dept Civil & Environm Engn Houston TX 77204 USA Oregon State Univ Dept Stat Corvallis OR 97331 USA Oregon State Univ Dept Math Corvallis OR 97331 USA Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Hubei Peoples R China

Optimization of short-term reservoir operation normally involves ramping constraints of outflows and water elevations at short time steps (e.g.,hourly). random search algorithms, such as genetic algorithms, have been widely used in optimization of reservoir operation. When applying random search algorithms to hourly reservoir operation, two important issues arise. The first one is the frequent violation of ramping constraints on the hourly reservoir outflows because of the random nature of the optimization algorithm. In other words, the optimization struggles to meet the ramping constraints when finding feasible solutions. The second issue is the zigzag fluctuation of the hourly decision variables as a result of the random search, which is unrealistic to implement in practice. In this study, the Savitzky-Golay smoothing filter (also known as least-squares filter) is incorporated periodically within the routine of the Nondominated Sorting Genetic algorithm (NSGA-II). The goal of this study is to smooth out the decision variable functions without deteriorating the performance of the optimization algorithm. The performance of the proposed approach is quantified through three indexes using a multireservoir system with 3,360 decision variables as the test case. The results show that use of the Savitzky-Golay filter not only provides a solution to the two aforementioned issues, but also significantly improves the performance of the NSGA-II for hourly reservoir operation. The optimal decisions obtained using the proposed approach display similar hourly variability to decisions of actual reservoir operation. (c) 2017 American Society of Civil Engineers.

关键词： random search algorithm Zigzag operational scheme Reservoir operation Savitzky-Golay filter Smoothing

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A simple method to find a robust output feedback controller by random search approach

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ISA TRANSACTIONS 2006年第1期45卷 35-44页

作者： Toscano, R CNRS Lab Tribol & Dynam Syst UMR 5513 ECLENISE F-42023 St Etienne 2 France

This paper presents a simple but effective method for finding a robust output feedback controller via a random search algorithm. The convergence of this algorithm can be guaranteed. Moreover, the probability to find a solution as well as the number of random trials can be estimated. The robustness of the closed-loop system is improved by the minimization of a given cost function reflecting the performance of the controller for a set of plants. Simulation studies are used to demonstrate the effectiveness of the proposed method. (c) 2006 ISA-The Instrumentation, Systems, and Automation Society.

关键词： output feedback pole placement random search algorithm robustness condition number cost function NP-hard problem

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2DOF multi-objective optimal tuning of disturbance reject fractional order PIDA controllers according to improved consensus oriented random search method

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JOURNAL OF ADVANCED REsearch 2020年 25卷 159-170页

作者： Ozbey, Necati Yeroglu, Celaleddin Alagoz, Baris Baykant Herencsar, Norbert Kartci, Aslihan Sotner, Roman Inonu Univ Dept Comp Engn Fac Engn Malatya Turkey Brno Univ Technol Fac Elect Engn & Commun Dept Telecommun Brno Czech Republic

This study presents a Fractional Order Proportional Integral Derivative Acceleration (FOPIDA) controller design methodology to improve set point and disturbance reject control performance. The proposed controller tuning method performs a multi-objective optimal fine-tuning strategy that implements a Consensus Oriented random search (CORS) algorithm to evaluate transient simulation results of a set point filter type Two Degree of Freedom (2DOF) FOPIDA control system. Contributions of this study have three folds: Firstly, it addresses tuning problem of FOPIDA controllers for first order time delay systems. Secondly, the study aims fine-tuning of 2DOF FOPIDA control structure for improved set point and disturbance rejection control according to transient simulations of implementation models. This enhances practical performance of theoretical tuning method according to implementation requirements. Thirdly, the paper presents a hybrid controller tuning methodology that increases effectiveness of the CORS algorithm by using stabilizing controller coefficients as an initial configuration. Accordingly, the CORS algorithm performs the fine-tuning of 2DOF FOPIDA controllers to achieve an improved set point and disturbance rejection control performances. This fine-tuning is carried out by considering transient simulation results of 2DOF FOPIDA controller implementation model. Moreover, Reference to Disturbance Ratio (RDR) formulation of the FOPIDA controller is derived and used for measurement of disturbance rejection control performance. Illustrative design examples are presented to demonstrate effectiveness of the proposed method. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Cairo University.

关键词： Fractional order control 2DOF controller design Disturbance rejection Reference to disturbance ratio random search algorithm

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2DOF multi-objective optimal tuning of disturbance reject fractional order PIDA controllers according to improved consensus oriented random search method

2DOF multi-objective optimal tuning of disturbance reject fr...

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作者： Özbey, Necati Brno University of Technology

关键词： Fractional order control 2DOF controller design Disturbance rejection Reference to disturbance ratio random search algorithm

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Design of computer network topologies: A Vroom Inspired Psychoclonal algorithm

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APPLIED MATHEMATICAL MODELLING 2013年第3期37卷 888-902页

作者： Shukla, Nagesh Dashora, Yogesh Tiwari, M. K. Shankar, Ravi Univ Warwick WMG Digital Lab Coventry CV4 7AL W Midlands England SMART Infrastruct Facil Wollongong NSW 2522 Australia Sabre Travel Technol Private Ltd Bangalore 560066 Karnataka India Indian Inst Technol Dept Ind Engn & Management Kharagpur 721302 W Bengal India Indian Inst Technol Dept Management Studies New Delhi India

In the prevailing era of network and communication technology, the problem pertaining to the determination of the most economic way to interconnect nodes while satisfying some reliability and quality of service constraints has been agnized as one of the most intricate and challenging problem for the modern day researchers and practitioners belonging to Communication and Networking community. Motivated by the improved performance of the concepts like proliferation, affinity maturation, receptor editing, etc., over the more prevalent generalized crossover and mutation;and by the application and effectiveness of Maslow's need hierarchy in combinatorial optimization as well the more logical motivational concepts provided by Vroom's valence expectancy theory, authors have proposed and investigated their applications to the topological design of distributed packet switched networks. The extensive computations over the problems of varying complexities and dimensions prove the superiority of the proposed methodology. It has been observed that the proposed Vroom Inspired Psychoclonal algorithm (VIPA) outperforms the traditional well established random search algorithms (i.e. Genetic algorithm, Simulated Annealing and Artificial Immune Systems) in the context of underlying problem;the performance being significantly improved as the problem complexity increases. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Communication and Networking random search algorithm Combinatorial optimization

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Robustness analysis and synthesis of a multi-PID controller based on an uncertain multimodel representation

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COMPUTERS & CHEMICAL ENGINEERING 2006年第2期31卷 66-77页

作者： Toscano, R. Lyonnet, P. ENISE ECL CNRS UMR 5513 Lab Tribol & Dynam Syst F-42023 St Etienne 2 France

This paper presents an effective method for robustness analysis and synthesis of a multi-PID controller for non-linear systems where desirable robustness and performance properties must be maintained across a large range of operating conditions. The robustness analysis problem is solved using an uncertain multimodel of the original non-linear system. The model of uncertainties used is an interval matrix modeled by a stochastic matrix which gives poor conservatism in the analysis of stability robustness. Moreover, the robust stability margin is interpreted as a smallest interval matrix that causes instability. This stability margin is evaluated using a random search algorithm. Simulation studies are used to demonstrate the effectiveness of the proposed method. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： PID controller multimodel multi-PID parametric uncertainties robust stability random search algorithm

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