Search Results - (( simulation optimization svm algorithm ) OR ( program implementation learning algorithm ))

Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…Right setting parameters are important to learning results and generalization ability of SVM. Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. …”

SVM driven approach for detecting DoS attacks in SDN environment by Najmun, Nisa, Adnan Shahid, Khan, Azman, Bujang Masli, Nusrat, Shaheen

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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

“…Finally, a novel hybrid Quantum-Inspired Evolutionary Programming - Least-Squares Support Vector Machine (QIEP-SVM) was presented. The results showed that the QIEP-SVM model had shown better prediction performance as compared to classical ANN, LS-SVM and QIEP-ANN.…”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…In the algorithm development a step-by-step example of the algorithm implementation is presented and then successfully implemented in Lego Mindstorm obstacle avoiding mobile robot as a proof of concept implementation of the hybrid AI algorithm. …”
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Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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Efficient and low complexity modulation classification algorithm for MIMO systems by Bahloul, M.R., Yusoff, M.Z., Saad, M.N.M.

“…The classification performance of the proposed algorithm was evaluated via extensive simulations under different operating conditions and was also compared with the one obtained with the optimal Hybrid Likelihood Ratio Test (HLRT) approach. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM) by Aziz N.F.A., Abdul Rahman T.K., Zakaria Z.

“…It also proposes a fast optimization algorithm for reactive power planning problem (RPP) through Fast Artificial Immune Support Vector Machine (FAISVM). …”

A new domain specific scripting language for automated machine learning pipeline by Masrom, S., Rahman, A.S.A., Omar, N., Baharun, N.

“…However, in respond to the implementation difficulty, there exists a limited software tool that support easy implementation for automated machine learning based on Genetic Programming. …”
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Rapid software framework for the implementation of machine learning classification models by Rahman, A.S.A., Masrom, S., Rahman, R.A., Ibrahim, R.

“…However, to implement a complete machine learning model involves some technical hurdles such as the steep learning curve, the abundance of the programming skills, the complexities of hyper-parameters, and the lack of user friendly platform to be used for the implementation. …”
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Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization by Nur Alia Shahira, Mohd Zaidi, Zuriani, Mustaffa, Muhammad Arif, Mohamad

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Implementation of advanced techniques in production and manufacturing sectors through support vector machine algorithm with embedded system by Rayner Alfred, Narender Chinthamu, T. Jayanthy, Elangovan Muniyandy, Tarun Kumar Dhiman, Nimmy John T.

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Open phase fault-tolerant support vector machine predictive power control for six-phase induction generator WECS by Hamoudi Y., Abdolrasol M.G.M., Amimeur H., Hassaini F., Ker P.J., Ustun T.S.

“…Then, open-phase localization is achieved using the Support Vector Machine (SVM) with hyperparameter Bayesian Optimization (BO). …”

Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

“…Actual data sets are collected from Ontario electricity market of the year 2017 for the verification of simulation results. Finally, the simulation results validated the premise of the proposed hybrid method through enhanced accuracy compared to the results acquired by implementing hybrid support vector machine (SVM) and hybrid ANN optimization methods. © 2013 IEEE.…”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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