Search Results - (( using optimization learning algorithm ) OR ( loading optimization svm algorithm ))

An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system by M. W., Mustafa, H., Shareef, M. H., Sulaiman, S. N., Abd. Khalid, S. R., Abd. Rahim, Omar, Aliman

“…The idea is to use GA as an optimizer to find the optimal values of hyper-parameters of LS-SVM and adopt a supervised learning approach to train the LS-SVM model. …”
Get full text
Get full text
Get full text

An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system by Mohd. Herwan, Sulaiman, Siti Rafidah, Abdul Rahim, Mohd Wazir, Mustafa, Hussain, Shareef, Dr., Saifulnizam, Abd. Khalid, Dr., Omar, Aliman

Get full text

Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm by Mohd Wazir, Mustafa, Dr., Saifulnizam, Abd. Khalid, Dr., Mohd Herwan, Sulaiman, Siti Rafidah, Abd Rahim, Omar, Aliman, Hussain, Shareef, Dr.

Get full text

Transmission loss allocation in deregulated power system using the hybrid genetic algorithm-support vector machine technique by M. W, Mustafa, Mohd Herwan, Sulaiman, H., Shareef, S. N., Abd. Khalid

Get full text

Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm by Mohd Wazir, Mustafa, Saifulnizam, Abd.Khalid, Mohd Herwan, Sulaiman, Siti Rafidah, Abd Rahim, Omar, Aliman, Shareef, Hussain

“…The idea is to use CGA to find the optimal values of regularization parameter, γ and Kernel RBF parameter, σ 2 , and adapt a supervised learning approach to train the LS-SVM model. …”
Get full text
Get full text
Get full text

Prediction of COVID-19 outbbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

“…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
Get full text
Get full text

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.

“…Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. …”

Specific heat capacity extraction of soybean oil/mxene nanofluids using optimized long short-term memory by Qazani, Mohammad Reza Chalak, Aslfattahi, Navid, Kulish, Vladimir Vladimirovich, Asadi, Houshyar, Schmirler, Michal, Zakarya, Muhammad, Alizadehsani, Roohallah, Haleem, Muhammad, Kadirgama, Kumaran

“…Notably, 95% of the recorded data via differential scanning calorimetry (DSC) is used for training machine learning techniques. In comparison, 5% is used for testing and validation purposes of the developed algorithm. …”
Get full text
Get full text
Get full text

Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification by Abdul Wahit, Mohamad Aizat

“…In this research, the LDA gives as higher as 85.8% of accuracy with six units of the sensors used compared to SVM which is 85% of accuracy percentage with five units of the sensors used. …”
Get full text
Get full text

Driver behaviour classification: a research using OBD-II data and machine learning by Muhamad Fadzil, Nur Farisya Aqilah, Mohd Fadzir, Hilda, Mansor, Hafizah, Rahardja, Untung

“…The suggested model in this study analyses driving behaviour using both supervised and unsupervised methods. The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. …”
Get full text
Get full text
Get full text
Get full text

Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

“…A one-year follow-up was conducted to monitor ACL injury, identifying n=11 injured players. Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
Get full text
Get full text

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

“…On top of that, the multiobjective QIEP is also applied to determine the optimal undervoltage load shedding (UVLS) in various loading conditions according to load profile with and without DG. …”
Get full text
Get full text

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.

“…FAISVM is a hybrid algorithm that incorporates the application of Artificial Immune System (AIS) and Support Vector Machine (SVM) in solving RPP problems. …”

Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
Get full text
Get full text
Get full text

An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
Get full text
Get full text

An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

“…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
Get full text
Get full text
Get full text

Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
Get full text
Get full text

Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

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

Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm by Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
Get full text
Get full text
Get full text