Search Results - ((((based algorithm) OR (_ algorithm))) OR (((means algorithm) OR (learning algorithms))))

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

Subjects: “…Genetic algorithms…”
Get full text
Get full text

Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…During the training process, bat algorithm is search the best one for number of neurons in hidden layer, learning rate and momentum rate which at the same time result the lowest mean absolute percentage error. …”
Get full text
Get full text

Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…During the training process, bat algorithm is search the best one for number of neurons in hidden layer, learning rate and momentum rate which at the same time result the lowest mean absolute percentage error. …”
Get full text
Get full text

Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
Get full text
Get full text
Get full text

Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques by Lipu M.S.H., Hussain A., Saad M.H.M., Hannan M.A.

“…Backpropagation algorithms; Errors; Learning algorithms; Mean square error; Neural networks; Particle swarm optimization (PSO); Torsional stress; Back propagation neural networks; Backtracking search algorithms; Heuristic optimization technique; Optimal neural network; Optimization algorithms; Particle swarm optimization algorithm; Root mean square errors; state of energy; Lithium-ion batteries…”

Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

Subjects: Get full text
Get full text

Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

Subjects:

Experimental implementation controlled SPWM inverter based harmony search algorithm by Najeeb M., Mansor M., Razali R., Daniyal H., Yahaya J.A.F.

“…C (programming language); Controllers; Electric inverters; Errors; Learning algorithms; MATLAB; Particle swarm optimization (PSO); Pulse width modulation; Voltage control; And transient response; C code for the sine PWM; C++ codes; Ezdsp f28335 board; Harmony search algorithm; Harmony search algorithms; Mean absolute error; Pulse width modulation inverters; Sinusoidal pulsewidth modulations (SPWM); Transient analysis…”

A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

“…In this paper, we propose a generalized RBF (GRBF) model to reduce the number of basis functions and thus alleviate curse of dimensionality. An EM-based training algorithm is also introduced, which uses fewer parameters compared to some classical supervised learning methods. …”
Get full text
Get full text
Get full text

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. Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
Get full text
Get full text

An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…Linear discriminant analysis (LDA) is a very popular method for dimensionality reduction in machine learning. Yet, the LDA cannot be implemented directly on unsupervised data as it requires the presence of class labels to train the algorithm. …”
Get full text
Get full text
Get full text

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

Subjects:

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
Get full text
Get full text

Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

Subjects:

Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

“…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
Get full text
Get full text

System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
Get full text
Get full text

Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan by Alwee, Razana, Sallehuddin, Roselina, Shamsuddin, Siti Mariyam

“…The results show that by using a small value of learning rate, Krzyzak algorithm is better than standard back propagation algorithm for medium and long term forecasting.…”
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.

Subjects:

Extremal region selection for MSER detection in food recognition by Razali, Mohd Norhisham, Manshor, Noridayu, Abdul Halin, Alfian, Mustapha, Norwati, Yaakob, Razali

“…Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
Get full text
Get full text
Get full text

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Empirical studies of metaheuristic algorithms performance demonstrated that the hybrid metaheuristic algorithms-artificial neural network outperformed the gradient-based artificial neural network (RMSE=113.92 m3/s) for streamflow forecasting, notably with the firefly approach, with an average RMSE=96.06 m3/s. …”
Get full text
Get full text
Get full text