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An analysis of the parameter modifications in varieties of harmony search algorithm
Published 2014“…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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Local search manoeuvres recruitment in the bees algorithm
Published 2011“…The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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An analysis of the parameter modifications in varieties of harmony search algorithm
Published 2014“…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting
Published 2015“…The importance of optimizing Least Squares Support Vector Machines (LSSVM) embedded control parameters has motivated researchers to search for proficient optimization techniques. …”
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Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter
Published 2017“…Agents interact among them to modify and enhance the solution throughout the search process. Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…The quantum calculus provides an extra degree of freedom to search the local and global minima by inducing a q-parameter. …”
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Inverse identification of elastic properties of composite materials using hybrid GA-ACO-PSO algorithm
Published 2018“…In the proposed algorithm, the effect of random initialization of GA is subdued by passing the products of GA through the ACO and PSO operators to well organize the exploitative and exploratory search coverage. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
Conference Paper -
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A modified weight optimisation for higher-order neural network in time series prediction
Published 2020“…Therefore, a modification was made by the additional step of information exchange between the top eggs, which significantly improve the convergence rate. Hence, motivated by the advantages of those Modified Cuckoo Search (MCS), the improvement of the MCS called Modified Cuckoo Search-Markov chain Monté Carlo (MCS-MCMC) learning algorithm is proposed for weight optimisation. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Dynamic replication algorithm in data grid: Survey
Published 2008“…Data replication is a common method used to improve the performance of data access in distributed systems. …”
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A Social Based Model For Genetic Algorithms.
Published 2007“…Genetic algorithms (GAs), as a general search model, have proved its success in several applications, however, recently, several researchers have argued that they have slow convergence; this slowness is due to the randomness in all their operations. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…Weakness such as trapped in local minima, slow convergence and finding a good rate between exploitation and exploration of the search space. This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Enhanced artificial bee colony for training least squares support vector machines in commodity price forecasting
Published 2014“…The importance of optimizing machine learning control parameters has motivated researchers to investigate for proficient optimization techniques.In this study, a Swarm Intelligence approach, namely artificial bee colony (ABC) is utilized to optimize parameters of least squares support vector machines.Considering critical issues such as enriching the searching strategy and preventing over fitting, two modifications to the original ABC are introduced. …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…To make the sensor more reliable, temperature data must be collected over the length of the cable, or distributed data rather than point data. …”
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Development of efficient t-way test data generation algorithm and execution strategies
Published 2012“…Hence, optimization in terms of number of generated test-data and execution time is in demand. Motivated by these, this thesis addresses the design, implementation and validation of four effective test data generation strategies in terms of 2-way and T-way as follows: (I) PS2Way (Pairwise Search for 2-way Test Data Generation) strategy is based on parameters pair technique. …”
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Design and Implementation of Data-at-Rest Encryption for Hadoop
Published 2017“…It is shown that the implementation of AES encryption algorithm is capable to secure data stored in HDFS to some extent.…”
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