Search Results - (( parameter evaluation tree algorithm ) OR ( parameter optimization learning algorithm ))

Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
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Water Quality Evaluation and Analysis by Integrating Statistical and Machine Learning Approaches by Amar Lokman, Wan Zakiah Wan Ismail, Nor Azlina Ab Aziz

Comprehensive comparison of various machine learning algorithms for short-term ozone concentration prediction by Yafouz A., AlDahoul N., Birima A.H., Ahmed A.N., Sherif M., Sefelnasr A., Allawi M.F., Elshafie A.

“…Forecasting; Learning algorithms; Machine learning; Monitoring; Neural networks; Ozone; Public health; Regression analysis; Air quality monitoring; Artificial neural network modeling; Gaussian process regression; Hyper-parameter; Hyper-parameter optimizations; Machine learning models; Ozone concentration; Ozone concentrations predictions; Quality monitoring system; Support vector regressions; Air quality…”

Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…Validation included both machine learning evaluation and expert feedback. Machine learning results showed strong performance, with Random Tree and PART delivering the most reliable predictions. …”
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Development of Anthro-Fitness Model for evaluating firefighter recruits’ performance readiness using machine learning by Borhanudin, Mohd Yusof @ Mohamed, Rabiu Muazu, Musa, Mohamad Nizam, Nazarudin, Anwar P. P., Abdul Majeed, Raj, Naresh Bhaskar, Mohd Azraai, Mohd Razman

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Development of anthro-fitness model for evaluating firefighter recruits' performance readiness using machine learning by Borhanudin, Mohd Yusof @ Mohamed, Rabiu Muazu, Musa, Mohamad Nizam, Nazarudin, Anwar P. P., Abdul Majeed, Raj, Naresh Bhaskar, Mohd Azraai, Mohd Razman

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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. …”
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Industrial implementation of machine learning forecasting algorithms for large-scale Solar Heat for Industrial Process (SHIP) Systems by Manu, Abdurrahman, Haja Mohideen, Ahmad Jazlan, Akhter, Muhammad Naveed, Ahmad Huzri, Muhammad Danial, Mohd Ibrahim, Azhar, Mohd Zaki, Hasan Firdaus, Sreeram, Victor

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Imbalanced multi-class power transformer fault data classification through Edited Nearest Neighbour-Manhattan-Random Forest by R Azmira, Putri Azmira

“…Furthermore, Random Forest is compared to four machine learning algorithms including Support Vector Machine, XGBoost, Convolutional Neural Networks, and Decision Trees. …”
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Near-infrared spectroscopy modeling of combustion characteristics in chip and ground biomass from fast-growing trees and agricultural residue by Shrestha, Bijendra, Posom, Jetsada, Pornchaloempong, Pimpen, Sirisomboon, Panmanas, Shrestha, Bim Prasad, Ariffin, Hidayah

“…This study focuses on the investigation and comparison of combustion characteristic parameters and combustion performance indices between fast-growing trees and agricultural residues as biomass sources. …”
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Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging by Mohd Ali, Maimunah

“…The results showed that the support vector machine achieved the best performance from the combination of optimal image parameters with the highest classification rate of 100 %. …”
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Tree-based contrast subspace mining method by Florence Sia Fui Sze

“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…This paper proposes optimal parameters for an extreme learning machine-based interval type 2 fuzzy logic system to learn its best configuration. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Although this algorithm is optimal for the parameters which appear linearly in the consequent part of interval type-2 fuzzy logic systems, it is not optimal for the parameters of the antecedent part as it uses random parameters. …”
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A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

“…The learning phase of wavelet neural network entails the task of finding the optimal set of parameter, which includes wavelet activation function, translation centers, dilation parameter, synaptic weight values, and bias terms. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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