Search Results - (( discrete optimization model algorithm ) OR ( parameter estimation method algorithm ))

Optimal model order selection for Transient Error Autoregressive Moving Average (TERA) MRI reconstruction method by Aibinu, Abiodun Musa, Najeeb, Athaur Rahman, Salami, Momoh Jimoh Emiyoka, Shafie, Amir Akramin

“…These criteria were evaluated on MRI data sets based on the method of Transient Error Reconstruction Algorithm (TERA). …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…A Monte Carlo simulation technique is examined and employed to overcome the computational issues arising from the intractability of the probability mass function of some mixed Poisson distributions. For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
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Optimal model order selection for transient error autoregressive moving average (TERA) MRI reconstruction method by Najeeb, Athaur Rahman, Salami, Momoh Jimoh Eyiomika, Aibinu, Abiodun Musa, Shafie, Amir Akramin

“…These criteria were evaluated on MRI data sets based on the method of Transient Error Reconstruction Algorithm (TERA). …”
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Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

“…A series of training patterns are constructed by employing between two images.Moreover,the work takes accomplishing maximum robustness and transparency into consideration.HPSO method is used to estimate the multiple parameters involved in the model. …”
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Identification of dynamic linear models of automotive palm bio-diesel engine for real-time speed control applications by Azuwir, Mohd Nor, Mohd Zaki, Ab. Muin, Prof. Dr., Abdul Hamid, Adom, Prof. Madya Dr.

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Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

“…These four algorithms can be used to solve discrete combinatorial optimization problems (COPs). …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…This thesis describes the development of an efficient algorithm for solving nonlinear stochastic optimal control problems in discrete-time based on the principle of model-reality differences. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

“…The optimized discrete DA is then applied to a TSP problem modelling a package delivery system in the area of Kuala Lumpur and to benchmark TSP problems. …”
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Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

“…The proposed algorithm in the retrieval phase showed optimal performance as compared to the baseline algorithms. …”
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Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

“…One of the alternatives to improve the modeling of the Discrete Hopfield Neural Network is by implementing different variants of logical rules. …”
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Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems by Mohd Zakimi, Zakaria, Hishamuddin, Jamaluddin, Robiah, Ahmad, Sayed Mohammad Reza, Loghmanian

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Advances in Particle Swarm Algorithms in Asynchronous, Discrete and Multi-Objective Optimization by Zuwairie, Ibrahim

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Solving SVM model selection problem using ACOR and IACOR by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization (ACO) has been used to solve Support Vector Machine (SVM) model selection problem.ACO originally deals with discrete optimization problem. …”
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Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network by Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin

“…It aimed to optimize the performance of G-type random high-order satisfiability logic structures embedded in Discrete Hopfield Neural Networks, thereby enhancing the efficiency of the Hopfield Neural Network learning algorithm. …”
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Dual optimization approach in discrete Hopfield neural network by Guo, Yueling, Zamri, Nur Ezlin, Mohd Kasihmuddin, Mohd Shareduwan, Alway, Alyaa, Mansor, Mohd. Asyraf, Li, Jia, Zhang, Qianhong

“…Having effective learning and retrieval phases of satisfiability logic in Discrete Hopfield Neural Network models ensures optimal synaptic weight management, which consequently leads to the production of optimal final neuron states. …”
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Incremental continuous ant colony optimization technique for support vector machine model selection problem by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem. …”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

“…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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FPGA implementation of metaheuristic optimization algorithm by Nurul Hazlina, Noordin, Phuah, Soon Eu, Zuwairie, Ibrahim

“…The Discrete SKF was then modeled using behavioral modeling to produce the Binary SKF which was then implemented onto FPGA. …”
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