Search Results - (( parameter optimization method algorithm ) OR ( using quality learning algorithm ))

Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
Get full text
Get full text
Get full text
Get full text

Optimization of balanced academic curriculum problem in educational institutions using teaching learning based optimization algorithm by Mohd Fadzil Faisae, Ab Rashid, Wasif, Ullah

“…This study aims to optimize BACP using the Teaching-Learning Based Optimization (TLBO) algorithm, addressing the limitations of existing approaches and providing an efficient framework for curriculum balancing. …”
Get full text
Get full text
Get full text

Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

“…The classification algorithm is a popular machine learning approach for software defect prediction. …”
Get full text
Get full text
Get full text

Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

“…We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
Get full text
Get full text
Get full text

Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

“…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
Get full text
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

“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
Get full text
Get full text
Get full text

Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
Get full text
Get full text

Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

“…This proposal discusses the techniques of optimizing and deploying machine learning algorithms on embedded devices for manufacturing applications; We investigate problems of printed circuit board (PCB) defects and artificial intelligence in embedded system. …”
Get full text
Get full text

Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…Therefore, prediction of laser machining cut quality, namely surface roughness was carried out using machine learning techniques based on Quick Back Propagation Algorithm using ANN. …”
Get full text
Get full text

A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Alam, Mohammad Nur‑E, Soudagar, Manzoore Elahi Mohammad

“…Integrating AI techniques with optimization algorithms, for instance, GA and Particle Swarm Optimization (PSO) significantly improves accuracy, enhancing parameter prediction and optimizing UW processes. …”
Get full text
Get full text
Get full text
Get full text

Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
Get full text
Get full text

Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
Get full text
Get full text
Get full text

Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…The cumbersome numerical computation and rudimentary empirical solutions hinder faster analysis over a wide range of parameters. However, machine and deep learning methods have higher accuracy but rely heavily on the quality and amount of training data, and the solution may become inconclusive if data is sparse. …”
Get full text
Get full text

A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Nur‑E‑Alam, Mohammad, Soudagar, Manzoore Elahi Mohammad

“…Integrating AI techniques with optimization algorithms, for instance, GA and Particle Swarm Optimization (PSO) significantly improves accuracy, enhancing parameter prediction and optimizing UW processes. …”
Get full text
Get full text
Get full text
Get full text
Get full text
Get full text

Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD by Bhandari, A.K., Soni, V., Kumar, A., Singh, G.K.

“…The method employs the ABC technique to learn the parameters of the adaptive thresholding function required for optimum enhancement. …”
Get full text
Get full text

Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach by Nur'atiah Zaini

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
Get full text
Get full text
Get full text

Wearables-assisted smart health monitoring for sleep quality prediction using optimal deep learning by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Alsolai, Hadeel, Gaddah, Abdulbaset, Othman, Mahmoud, Yaseen, Ishfaq, Rizwanullah, Mohammed, Zamani, Abu Sarwar

“…To enhance the sleep quality prediction performance of the DBN model, the enhanced seagull optimization (ESGO) algorithm is used for hyperparameter tuning. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions by Reza M.S., Hannan M.A., Ker P.J., Mansor M., Lipu M.S.H., Hossain M.J., Mahlia T.M.I.

Subjects: