Search Results - (( evolution classification system algorithm ) OR ( data estimation method algorithm ))

Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…The proposed system utilizes Biased ARTMAP for pattern learning and classification. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

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Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

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Analysis on target detection and classification in LTE based passive forward scattering radar by Raja Abdullah, Raja Syamsul Azmir, Abdul Aziz, Noor Hafizah, Abdul Rashid, Nur Emileen, Salah, Asem Ahmad, Hashim, Fazirulhisyam

“…The experimental results confirm the passive FSR system’s capability for ground target detection and classification. …”
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Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

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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

“…It will help the researcher get the fitted graph model, correct data, and estimate the value based on the data’s behaviour. …”
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Semiparametric estimation with profile algorithm for longitudinal binary data by Suliadi, Suliadi, Ibrahim, Noor Akma, Daud, Isa

“…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems by Muhammad Akmal, Remli, Mohd Saberi, Mohamad, Safaai, Deris, Sinnott, Richard O., Suhaimi, Napis

“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…The simulation study results and real data sets indicate that the proposed MRFCHCS+LAD-SCAD estimator was found to be the best method compared to other methods in this study.…”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems by Remli, Muhammad Akmal, Mohamad, Mohd Saberi, Deris, Safaai, Sinnott, Richard, Napis, Suhaimi

“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions by Adday, Ghaihab Hassan, K. Subramaniam, Shamala, Ahmad Zukarnain, Zuriati, Samian, Normalia

“…Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

“…And developing a quick and accurate model could help in detecting pests and diseases in plants. Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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State estimation of the power system using robust estimator by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Firuzabad, M.F.

“…In the existence of gross errors, the proposed algorithm provides estimates as good as those that are achieved by the conventional method of the WLS when no gross error exists in the process data. …”
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