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ICSOMPA: A novel improved hybrid algorithm for global optimisation

EVOLUTIONARY INTELLIGENCE 2024年第5-6期17卷 3337-3440页

作者： Mohammed, Usman Karataev, Tologon Oshiga, Omotayo Oghorada, Oghenewvogaga Adeshina, Steve A. Hussein, Suleiman U. Abualigah, Laith Galadima, Ahmadu Abubakar, Dayyabu Sanusi, Jaafaru Nile Univ Nigeria Elect & Elect Engn Dept Abuja Nigeria Nile Univ Nigeria Comp Engn Dept Abuja Nigeria Nile Univ Nigeria Civil Engn Dept Abuja Nigeria Al Al Bayt Univ Comp Sci Dept Mafraq 25113 Jordan Univ Tabuk Artificial Intelligence & Sensing Technol AIST Res Ctr Tabuk 71491 Saudi Arabia Al Ahliyya Amman Univ Hourani Ctr Appl Sci Res Amman 19328 Jordan Middle East Univ MEU Res Unit Amman 11831 Jordan Lebanese Amer Univ Dept Elect & Comp Engn Byblos 135053 Lebanon Appl Sci Private Univ Appl Sci Res Ctr Amman 11931 Jordan Sunway Univ Malaysia Sch Engn & Technol Petaling Jaya 27500 Malaysia

The Marine Predators algorithm (MPA) is among the recently proposed metaheuristic algorithms (MAs), and it got its inspiration from the ocean predators' foraging behaviour based on Brownian and Levy motions. Good exploration, convergence accuracy, ease of implementation, easy parameter settings, fewer parameters, etc., are some of its strengths. Nevertheless, it experiences premature convergence and local optima trapping sometimes. The Competitive Swarm Optimiser (CSO) is a Particle Swarm Optimiser (PSO) variant. It got its inspiration from the social groups' collective decision-making and social behaviour. Good exploitation, a balance between exploitation and exploration, low premature convergence, algorithmic simplicity, etc., are some of its strengths. However, it has a loss of diversity and premature convergence. Aiming at solving the MPA's weaknesses and utilising the complementary strengths of MPA and CSO, an improved hybrid MPA has been proposed and it's named ICSOMPA. The MPA was first improved by utilising a chaotic mapping strategy for the MPA initialisation, utilising an adaptive convergence factor (CF) for step size control aiming at striking a balance between local exploitation and global exploration, utilising the Weibull distribution in place of Brownian motion aiming at preventing algorithm local trapping, and utilising chaotic sequences in the MPA's early stages as opposed to using random numbers to avoid overlap and uneven agent distribution. The improved MPA was then hybridised with the CSO aiming at leveraging the MPA's and CSO's strengths to provide higher convergence accuracy, convergence speed, and avoiding local optima trapping. The proposed algorithm's performance was tested and validated using the Congress on Evolutionary Computation (CEC) suites and engineering design problems. The CEC2014, CEC2017, CEC2020, CEC2022, and the 3 most employed engineering design problems have been utilised. Six different sets of experiments have been conducte

关键词： CSO Hybrid ICSOMPA improved MPA algorithm

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Optimized deployment of a radar network based on an improved firefly algorithm

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Frontiers of Information Technology & Electronic Engineering 2019年第3期20卷 425-437页

作者： Xue-jun ZHANG Wei JIA Xiang-min GUAN Guo-qiang XU Jun CHEN Yan-bo ZHU National Key Laboratory of CNS/ATM School of Electronic and Information EngineeringBeihang University Department of General Aviation Civil Aviation Management Institute of China Lincoln School of Engineering University of LincolnBrayford Pool Campus

The threats and challenges of unmanned aerial vehicle(UAV) invasion defense due to rapid UAV development have attracted increased attention recently. One of the important UAV invasion defense methods is radar network detection. To form a tight and reliable radar surveillance network with limited resources, it is essential to investigate optimized radar network deployment. This optimization problem is difficult to solve due to its nonlinear features and strong coupling of multiple constraints. To address these issues, we propose an improved firefly algorithm that employs a neighborhood learning strategy with a feedback mechanism and chaotic local search by elite fireflies to obtain a trade-off between exploration and exploitation abilities. Moreover, a chaotic sequence is used to generate initial firefly positions to improve population diversity. Experiments have been conducted on 12 famous benchmark functions and in a classical radar deployment scenario. Results indicate that our approach achieves much better performance than the classical firefly algorithm(FA) and four recently proposed FA variants.

关键词： improved firefly algorithm Radar surveillance network Deployment optimization Unmanned aerial vehicle (UAV) invasion defense

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An improved Immune algorithm for Solving Path Optimization Problem in Deep Immune Learning of Gene Network

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Journal of Computer and Communications 2019年第12期7卷 166-174页

作者： Tao Gong Mengyuan Wang College of Information Science & Technology Donghua University Shanghai China

In order to overcome some defects of the traditional immune algorithm, the immune algorithm was improved for solving a path optimization problem in deep immune learning of a gene network. Firstly, the diversity of the solution population was enhanced in the evolution process by improving the memory cell processing method. Moreover, effective gene information was dynamically extracted from the genes of the excellent antibodies to make good vaccines in the process of immune evolution. Worse antibodies were optimized by vaccinating these antibodies, and the convergence of the immune algorithm to the optimal solution was improved. Finally, the feasibility of the improved immune algorithm was verified in the experimental simulation for solving the classic NP problem in deep immune learning of the gene network.

关键词： improved Immune algorithm Path Optimization Memory Cell Processing Vaccine

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Investigate the kinetics of coke solution loss reaction with an alkali metal as a catalyst based on the improved genetic algorithm

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International Journal of Coal Science & Technology 2018年第4期5卷 430-438页

作者： Zhao Lei Yunhe Zhang Ping Cui Anhui Key Laboratory of Coal Clean Conversion and Utilization School of Chemistry and Chemical EngineeringAnhui University of TechnologyMa'anshan City 243002China

The kinetics of coke solution loss reaction with and without sodium carbonate were investigated under the reaction atmosphere of carb on dioxide. The variables of gas flow rate and coke particle size were explored to eliminate the external and inteirial diffusion, respectively. Then, the improved method combining with the least square and the genetic algorithm was proposed to solve the homogeneous model and the shrinking core model. It was found that the improved genetic algorithm method has good stability by studying the fitness function at each generation. In the homogeneous model, the activation energy with and without sodium carbonate was 54.89 and 95.56 kJ/mol, respectively. And. the activation energy with and without sodium carbonate in the shrinking core model was 49.83 and 92.18 kJ/mol, respectively. Therefore, it was concluded that the sodium carbonate has the catalytic action. In addition, results showed that the estimated conversions were agreed well with the experimental ones, which indicated that the calculated kinetic parameters were valid and the proposed method was successfully developed.

关键词： Coking Kinetic improved genetic algorithm Alkali metal Catalyst

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An improved Apriori algorithm Based on an Evolution-Communication Tissue-Like P System with Promoters and Inhibitors

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DISCRETE DYNAMICS IN NATURE AND SOCIETY 2017年第Pt.1期2017卷 6978146-1-6978146-11页

作者： Liu, Xiyu Zhao, Yuzhen Sun, Minghe Shandong Normal Univ Coll Management Sci & Engn Jinan Shandong Peoples R China Univ Texas San Antonio Coll Business San Antonio TX USA

Apriori algorithm, as a typical frequent itemsets mining method, can help researchers and practitioners discover implicit associations from large amounts of data. In this work, a fast Apriori algorithm, called ECTPPI-Apriori, for processing large datasets, is proposed, which is based on an evolution-communication tissue-like P system with promoters and inhibitors. The structure of the ECTPPI-Apriori algorithm is tissue-like and the evolution rules of the algorithm are object rewriting rules. The time complexity of ECTPPI-Apriori is substantially improved from that of the conventional Apriori algorithms. The results give some hints to improve conventional algorithms by using membrane computing models.

关键词： improved Apriori algorithm P Blood-Group System algorithms Computational Molecular Biology RECOVERY CATEGORY

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NASA Technical Reports Server (Ntrs) 20080000844: an improved algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

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2017年

NASA Technical Reports Server (Ntrs) 20080000844: an improved algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements by NASA Technical Reports Server (Ntrs); published by

关键词： (ntrs) 20080000844: algorithm algorithms bias cess, robert d. clouds (meteorology) downwelling earth sciences gupta, shashi k. ice clouds improved kratz, david p. long wave radiation modis (radiometry) nasa technical reports server (ntrs) precipitation radiant flux density radiative transfer satellite observation surface radiation budget project systematic errors terra spacecraft upwelling water water vapor wilber, anne c. zhou, yaping

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NASA Technical Reports Server (Ntrs) 20080040138: an improved algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

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2017年

NASA Technical Reports Server (Ntrs) 20080040138: an improved algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements by NASA Technical Reports Server (Ntrs); published by

关键词： (ntrs) 20080040138: alaska algorithm algorithms ceres (experiment) cess, robert d. clouds (meteorology) downwelling gupta, shashi k. ice environments improved kratz, david p. long wave radiation meteorology nasa technical reports server (ntrs) radiometers satellite observation systematic errors terrestrial radiation wilber, anne c. zhou, yaping

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NASA Technical Reports Server (Ntrs) 19900004432: an improved algorithm for the Modeling of Vapor Flow in Heat Pipes

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2017年

NASA Technical Reports Server (Ntrs) 19900004432: an improved algorithm for the Modeling of Vapor Flow in Heat Pipes by NASA Technical Reports Server (Ntrs); published by

关键词： (ntrs) 19900004432: algorithm algorithms computer programs evaporators hainley, donald c. heat pipes improved incompressible flow mathematical models modeling nasa technical reports server (ntrs) pipe flow pressure distribution spacecraft radiators temperature profiles tower, leonard k. velocity distribution working fluids

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On the Optimization of improved Apriori algorithm via Linked-list Trie 17

On the Optimization of Improved Apriori Algorithm via Linked...

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International Conference on Big Data Research (ICBDR)

作者： Mlambo, Mercy Gasela, Naison Esiefarienrhe, Michael Isong, Bassey North West Univ Dept Comp Sci Mafikeng South Africa

ISBN: (纸本)9781450353564

In recent years there has been explosive growth of data and its utilization triggered by technological advancements. Consequently, several business enterprises have accumulated enormous data from client purchases gathered at all times. Data mining involve processes used to turn raw data into beneficial information through the use of suitable software and hardware. This area has attracted significant attention and several different approaches exist such as association rules (AR). In particular, AR constitutes an important data mining approach but is faced with several challenges in terms of efficiency. Therefore, this paper investigates the major challenges based on AR in data mining stemming from the improvement of the apriori algorithm. We aim towards reducing the major shortcomings of the current apriori algorithm. This paper also proposes the usage of an optimized linked-list trie data structure for storage and to make support counting more efficient. To achieve this, an effective candidate generation method was employed to reduce the cost of matching candidate itemsets. The improved and the optimized apriori algorithm and its benefits are presented and discussed in this paper.

关键词： algorithm Apriori Itemsets improved Linked-list trie Data mining

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An improved Search algorithm to Find G-Quadruplexes in Genome Sequences

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2016年

An improved Search algorithm to Find G-Quadruplexes in Genome Sequences by Anna Varizhuk; Dmitry Ischenko; Igor Smirnov; Olga Tatarinova; Vyacheslav Severov; Roman Novikov; Vladimir Tsvetkov; Vladimir Naumov; Dmitry K... 详细信息

关键词： algorithm bioinformatics genome g-quadruplexes improved search

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