Search Results - (( using optimization based algorithm ) OR ( parameter extending learning algorithm ))

Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

“…With various optimization algorithms available, choosing the one that best suits the deep learning model and dataset can make a substantial difference in achieving optimal results. …”
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Vision based automatic steering control using a PID controller by Abdullah, A.S., Hai, L.K., Osman, N.A.A., Zainon, M.Z.

“…This is then extended to incorporate iterative learning control with genetic algorithm (GA) to optimize the learning parameters and a feedforward controller based on input shaping techniques for control of vibration (flexible motion) of the system. …”
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Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi by Mohd Azmi, Nur Amirah

“…Traditional methods struggle to model these complexities effectively, necessitating adoption of advanced algorithms to improve accuracy. The aim of this project is to develop a Diamond Price Prediction System using Random Forest, designed to accurately predict diamond prices based on attributes. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Saleh, Basma Jumaa, Omar, Zaid, As’ari, Muhammad Amir, Bhateja, Vikrant, Izhar, Lila Iznita

“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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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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Hybrid learning control schemes with input shaping of a flexible manipulator system. by Md. Zain, M. Z., Tokhi, M. O., Mohamed, Z.

“…A collocated proportional-derivative (PD) controller utilizing hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate iterative learning control with acceleration feedback and genetic algorithms (GAs) for optimization of the learning parameters and a feedforward controller based on input shaping techniques for control of vibration (flexible motion) of the system. …”
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Performance of hybrid learning control with input shaping for input tracking and vibration suppression of a flexible manipulator by Md. Zain, M. Z., Tokhi, M. O., Mohamed, Z.

“…This Is Then Extended To Incorporate Iterative Learning Control With Genetic Algorithm (GA) To Optimize The Learning Parameters And A Feedforward Controller Based On Input Shaping Techniques For Control Of Vibration (Flexible Motion) Of The System. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…Supervised and unsupervised machine learning algorithms particularly the Support Vector Machine (SVM) and Density Based Spatial Clustering of Application with Noise (DBSCAN) are used in this study. …”
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A systematic design of interval type-2 fuzzy logic system using extreme learning machine for electricity load demand forecasting by Hassan, S., Khosravi, A., Jaafar, J., Khanesar, M.A.

“…The ELM strategy ensures fast learning of the IT2FLS as well as optimality of the parameters. …”
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network by Wen, Dong, Li, Rou, Tang, Hao, Liu, Yijun, Wan, Xianglong, Dong, Xianling, Saripan, M. Iqbal, Lan, Xifa, Song, Haiqing, Zhou, Yanhong

“…Secondly, to enhance feature propagation and reduce the number of parameters, the dense network was connected after the multi-scale convolutional network, and the learning rate change function of the stochastic gradient descent algorithm was optimized to objectively evaluate the training effect. …”
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A Hybrid Gini PSO-SVM Feature Selection: An Empirical Study of Population Sizes on Different Classifier by Noormadinah Allias, Megat NorulAzmi Megat Mohamed Noor, Mohd. Nazri Ismail, Kim de Silva, (UniKL MIIT)

“…A performance of anti-spam filter not only depends on the number of features and types of classifier that are used, but it also depends on the other parameter settings. Deriving from previous experiments, we extended our work by investigating the effect of population sizes from our proposed method of feature selection on different learning classifier algorithms using Random Forest, Voting, Decision Tree, Support Vector Machine and Stacking. …”

An extended adaptive mechanism of evolutionary based channel assignment via reinforcement by Teo, Kenneth Tze Kin, Yew, Hoe Tung, Lye, Scott Carr Ken, Lim, Kit Guan, Ang, Soo Siang, Khairul Anuar Mohamad, Ali Chekima, Liau, Chung Fan, Aroland Jilui Kiring

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Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid by Wahid, Muhammad Hazim

“…One of the major challenges when applying machine learning is to identify the best algorithm from a variety of algorithms to solve a problem. …”
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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

“…However, including more representative samples and exploring a more suitable machine learning algorithm are essential for updating the model to achieve a better nondestructive assessment of biomass combustion behavior.…”
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Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

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Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting by Wei Y., Hashim H., Chong K.L., Huang Y.F., Ahmed A.N., El-Shafie A.

Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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