Search Results - (( data directed learning algorithm ) OR ( data optimization method algorithm ))

A direct ensemble classifier for imbalanced multiclass learning by Sainin, Mohd Shamrie, Alfred, Rayner

“…Researchers have shown that although traditional direct classifier algorithm can be easily applied to multiclass classification, the performance of a single classifier is decreased with the existence of imbalance data in multiclass classification tasks.Thus, ensemble of classifiers has emerged as one of the hot topics in multiclass classification tasks for imbalance problem for data mining and machine learning domain.Ensemble learning is an effective technique that has increasingly been adopted to combine multiple learning algorithms to improve overall prediction accuraciesand may outperform any single sophisticated classifiers.In this paper, an ensemble learner called a Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) that combines simple nearest neighbour and Naive Bayes algorithms is proposed. …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. In order to justify the acceptability of this method, we have implemented this model on three different standard datasets. …”
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…Hence, a differential search algorithm (DSA) is employed to search for the optimal values of trees and leaves in the RFR algorithm. …”

A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

“…Besides that, the experiment shows that agent which learning sequential data has earned lower precision by 17.57% and novelty by 4.68% compared to the agent that without learning sequential data, however, it achieved better diversity by 2.66%. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…An alternative method is proposed, utilizing machine learning algorithms. …”

Virtual power plant and microgrids controller for energy management based on optimization techniques by Abdolrasol M.G.M., Mohamed A., Hannan M.A.

Applications of machine learning to friction stir welding process optimization by Nasir, Tauqir, Asmaela, Mohammed, Zeeshan, Qasim, Solyali, Davut

“…Machine learning (ML) is a branch of artificial intelligent which involve the study and development of algorithm for computer to learn from data. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…Hence, this research has proposed three enhanced frameworks, namely, Optimized Gravitational-based (OGC), Density-Based Particle Swarm Optimization (DPSO), and Variance-based Differential Evolution with an Optional Crossover (VDEO) frameworks for data clustering. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

“…Several researchers have reported different optimization methods for blade parameters such as Blade Element Momentum theory (BEM), Computational Fluid Dynamics (CFD) and Supervisory Control and Data Acquisition (SCADA) system. …”
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Study on tourism development using CRITIC method for tourist satisfaction by Yang, Xi, Ali, Noor Azman, Hon Tat, Huam

“…This paper presents a novel approach for evaluating tourist satisfaction and developing optimized strategies by integrating the CRITIC method, deep learning with Multilayer Perceptron (MLP), and Genetic Algorithms (GA). …”
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A review and comparative analysis of predictive models for supply chain demand forecasting by Ibrahim Ahmed Omer, Rehab, Hassan, Raini, S. Abd. Aziz, Madihah

“…This study reviews key techniques, including statistical time-series models, supervised and unsupervised learning algorithms, ensemble methods, and deep learning architectures. …”
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Hierarchical extreme learning machine based reinforcement learning for goal localization by AlDahoul, Nouar, Htike, Zaw Zaw, Akmeliawati, Rini

“…This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. …”
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Artificial intelligence (AI) and its application in architecture design: a thematic review by Jin, Deran, Zairul, Mohd, Salih, Sarah Abdulkareem

“…Hence, this study specifically aimed to retrospectively analyze AI’s impact on architectural design and explore the evolving trends within AI-based architectural design using thematic review (TreZ) method. Data for this research encompassed a thematic review of 54 publications spanning from 2019 to 2023. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…Hitherto, the majority of computer vision approaches have been focused on designing sophisticated algorithms to achieve a robust feature representation for plant data. …”
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Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

“…The constrained layer enables the CNN model to learn the required features directly from ubiquitous image input and then performs classification. …”
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Condition monitoring of deep drilling process for cooling channel making in hot press die by Muhamad Aslam, Abdul Raub

“…To classify this data, machine learning method such as Support Vector Machine (SVM) and Artificial Neural Network (ANN) was employed. …”
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