Search Results - (( initial solution method algorithm ) OR ( variable selection based algorithm ))

Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul by Siaw Ying Doreen, Sek

“…The VNS algorithm is used to improve the obtained solutions in the improvement phase. …”
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness by Noori, Mustafa Sabah, Sahbudin, Ratna K.Z., Sali, Aduwati, Hashim, Fazirulhisyam

“…Additionally, our method employs an improved initialization phase using equal sampling for each decision variable to ensure a comprehensive exploration of the entire solution space. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

“…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…Modeling of hydrological process has been increasingly complicated since we need to take into consideration an increasing number of descriptive variables. In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah by Aziz Shah, Mohamad Azam Shah

“…The SMU method based on the improved model was used to predict the variability of the dynamic behaviour of the structure. …”
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Modelling of Adsorption of Dyes from Aqueous Solution by Activated Carbon by Wong, Teck Ngin

“…These v sets of ODEs are then integrated using the numerical algorithm DIVPAG (IMSL library subroutine), which is based on variable order, variable step method implementing backward differential formula (Gear’s Method) and is suitable for stiff system of first order non-linear ODEs. …”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In addition, experiments prove that incremental genetic-based clustering ensemble algorithm speed up to converge into an optimal clustering solution, where pattern ensemble learning method and the cluster partitions produced by the threshold fuzzy c-means clustering algorithm are employed as recombination operator and initial population, respectively.…”
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Multistage optimal homotopy asymptotic method for solving initial-value problems by Anakira, N. R., Alomari, A. K., Jameela, Ali, Hashim, Ishak

“…In this paper, a new approximate analytical algorithm namely multistage optimal homotopy asymptotic method (MOHAM) is presented for the first time to obtain approximate analytical solutions for linear, nonlinear and system of initial value problems (IVPs).This algorithm depends on the standard optimal homotopy asymptotic method (OHAM), in which it is treated as an algorithm in a sequence of subinterval. …”
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Combining approximation algorithm with genetic algorithm at the initial population for NP-complete problem by Razip, H., Zakaria, M.N.

“…In Genetic Algorithm (GA), the prevalent approach to population initialization are heuristics and randomization. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

“…The variable block matching developed based on four stages which is the video and frame selection, threshold calculation, block size selection and search pattern. …”
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Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation by Tan , Khang Siang

“…Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”

A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin by Baharuddin, Ramizah

“…Newton's Method also called the Newton-Raphson method is a recursive algorithm for approximating the root of a differentiable function. …”
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Shooting method with root finding to solve boundary value problems / Aryani Rima Matakim by Matakim, Aryani Rima

“…This method involves guessing initial conditions and iteratively adjusting them until the solution satisfies the boundary conditions at the other end of the domain. …”
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

“…We develop Robust Forward Selection algorithm based on RFCH correlation coefficient (RFS.RFCH) because FS.Winso is not robust to multivariate outliers. …”
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Enhancing the RC4 algorithm by eliminating the Initiative Vector (IV) transmission by Waleed Abdelrahman Yousif Mohammed, Salmah Fattah, Khalid Mohammed Osman Saeed, Ashraf Osman Ibrahim Elsayed, Safaa Eltahier

“…This paper introduces an innovative approach to address the vulnerabilities of the RC4 encryption algorithm by employing an Initiative Vector (IV). The proposed method incorporates a lengthy random text without transmitting an initialization vector. …”
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