Search Results - (( java application bee algorithm ) OR ( parameter implementation some algorithm ))

A novel normal parameter reduction algorithm of soft sets by Ma, Xiuqin, Norrozila, Sulaiman, Qin, Hongwu, Herawan, Tutut

“…The comparison result on a Boolean-valued dataset shows that, the proposed algorithm involves relatively less computation and is easier to implement and understand as compared with the soft set-based algorithm of normal parameter reduction.…”
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Three-term backpropagation algorithm for classification problem by Saman, Fadhlina Izzah

“…This algorithm utilizes two term parameters which are Learning Rate, α and Momentum Factor,β. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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An improved back propagation leaning algorithm using second order methods with gain parameter by Mohd Nawi, Nazri, Mohamed Saufi, Noor Haliza, Budiyono, Avon, Abdul Hamid, Noorhamreeza, Rehman Gillani, Syed Muhammad Zubair, Ramli, Azizul Azhar

“…It has successfully been implemented in various practical problems. However, the algorithm still faces some drawbacks such as getting easily stuck at local minima and needs longer time to converge on an acceptable solution. …”
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Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles by Ihsan, Afdhalul, Rainarli, Ednawati

“…This study examined PSO to optimize the k-Nearest Neighbour (k-NN) algorithm's performance in categorizing news articles. k-NN is an algorithm that is simple and easy to implement. …”
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Fuzzy state space modeling for solving inverse problems in multivariable dynamic systems by Ismail, Razidah

“…To facilitate the implementation of these algorithms, a semi-automated computational tool using Matlab® programming facilities is developed. …”
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Workability review of genetic algorithm approach in networks by Nurika, O., Zakaria, N., Hassan, F., Jung, L.T.

“…Generally, genetic algorithm process will accomplish according to its parameters sizes. …”
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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

“…Although useful, all aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. In the case of reactive systems, such an assumption is invalid as some parameter operations, or events, occur in sequence and hence, creating a possibility of bugs or faults triggered by the order, or sequence, of input parameters. …”
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ANALYSIS AND INTERPRETATION OF PRESSURE TRANSIENT TEST DATA BY RECENT ROBUST DECONVOLUTION METHODS by Mohd Mustafa, Muhammad Izzatullah

“…In this work, by using the recent robust deconvolution algorithm of Pimonov et al. and/or the ones implemented in Weatherford PanSystem Well Test Software, the effects of the algorithmic parameters (including error levels in pressure and rate data, and the curvature constraint value) as well as the initial pressure on the deconvolved responses are investigated. …”
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Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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A bit-serial architecture for a multiplierless DCT by Choomchuay, S., Timakul, S.

“…Varying data word length, MSE obtained form our approach and some similar algorithms are also investigated and reported.…”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi by Hayawi, Mustafa Jabbar

“…EHA are known to have nonlinear parameters and dynamic factors such as frictions, load variations and leakage. …”
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Computing the autopilot control algorithm using predictive functional control for unstable model by H. A., Kasdirin, J. A., Rossiter

“…Hence, designed PFC algorithm need to find the suitable tuning parameters as its play an important part of the designing the autopilot controller. …”
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SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR by FUNG , CHUN TING

“…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e by Anuar, Ammar

“…Each AC has its own queue and set of EDCA parameter values. Although IEEE 802.11e has been widely implemented in commercial hardware, the EDCA parameters are normally preset with some default values recommended by the standard. …”
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A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

“…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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Marine Predator Algorithm and Related Variants: A Systematic Review by Philibus, Emmanuel, Mohd Zain, Azlan, Prasetya, Didik Dwi, Bahari, Mahadi, Yusup, Norfadzlan, Abdul Jalil, Rozita, Abdul Majid, Mazlina, A Samah, Azurah

“…Findings reveal several search strategies implemented to improve the algorithm’s performance. …”
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