Search Results - (( using optimization model algorithm ) OR ( pattern selection method algorithm ))

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. …”
Get full text
Get full text
Get full text

Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
Get full text
Get full text
Get full text

Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
Get full text
Get full text
Get full text

Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…Negative Selection algorithm (NSA), Clonal Selection algorithm (CSA) and Immune Network algorithm (INA); and model analysis. …”
Get full text
Get full text
Get full text

An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
Get full text
Get full text

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

“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
Get full text
Get full text

Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…Complementing this, the Harmony Search Algorithm (HSA) is incorporated to augment data features, facilitating better pattern recognition and enhancing overall classification accuracy through optimized feature engineering. …”
Get full text
Get full text
Get full text

Computational dynamic support model for social support assignments around stressed individuals among graduate students by Al-Shorman, Roqia Rateb

“…The algorithm complexity analysis was used to measure the execution time in the worst case. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Identifying diseases and diagnosis using machine learning by Iswanto I., Laxmi Lydia E., Shankar K., Nguyen P.T., Hashim W., Maseleno A.

“…For classify the disease classification algorithms are used. It uses are many dimensionality reduction algorithms and classification algorithms. …”

Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…Cuckoo search), and evaluator or model inducing algorithms (e.g SVM) were utilized for feature subset selection, which further compared to select the optimal conditioning factors subset. …”
Get full text
Get full text

Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

“…In making a forecast for energy demand, accuracy is the primary criteria in selecting among forecasting techniques. Time Series method has always been used in a variety of forecasting applications. …”
Get full text
Get full text

Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain by Ong, Pauline, Tieh, Tony Hieng Cai, Lai, Kee Huong, Lee, Woon Kiow, Ismon, Maznan

“…Second, the MFO algorithm was utilised to select the optimal discriminative features. …”
Get full text
Get full text
Get full text

CUCKOO SEARCH OPTIMIZATION NEURAL NETWORK MODELS FOR FORECASTING LONG-TERM PRECIPITATION by Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Khairul Anwar, Mohamad Said

“…This paper presents the application of a novel optimization algorithm, Cuckoo Search Optimization (CSO), to train feedforward neural networks to forecast long-term precipitation using three climate models, namely HadCM3, ECHAM5, and HadGEM3‐RA. …”
Get full text
Get full text
Get full text

Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…Experimentally observed responses were used to train, map and optimize the network algorithms before the best architecture was selected. …”
Get full text
Get full text

Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

“…A Lipschitz method and Leven berg Marquardt algorithm is used to determine the model order number and train the network respectively. …”
Get full text
Get full text

Improving neural networks training using experiment design approach by Chong, Wei Kean

“…Randomly select the m data set for conventional training algorithm. …”
Get full text
Get full text

A Harris hawks optimization based single- and multi objective optimal power flow considering environmental emission by Islam, Mohammad Zohrul, Abdul Wahab, Noor Izzri, Veerasamy, Veerapandiyan, Hizam, Hashim, Mailah, Nashiren Farzilah, Guerrero, Josep M., Mohd Nasir, Mohamad Nasrun

“…The obtained results are compared with the other Artificial Intelligence (AI) techniques such as the Whale Optimization Algorithm (WOA), the Salp Swarm Algorithm (SSA), Moth Flame (MF) and Glow Warm Optimization (GWO). …”
Get full text
Get full text
Get full text

A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
Get full text
Get full text
Get full text

Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization by Fatai Adesina, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem

“…Traditionally, petroleum and natural gas engineers rely on “rules-of-thumb” in the selection of optimal features with much disregard to the hidden patterns in operational data. …”
Get full text
Get full text
Get full text

Derivation of radiative transfer parameters using image-based technique / Wan Noniafida Ab Manan by Ab Manan, Wan Noniafida

“…However, maritime model and NIR band shows the opposite pattern of the established model. …”
Get full text
Get full text