Search Results - (( java implication _ algorithm ) OR ( using partial ((using algorithm) OR (learning algorithm)) ))

Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training by Lee, Sen Tan, Zainuddin, Zarita, Ong, Pauline

“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…These DRL-based algorithms optimize the local and global maximum power point (MPP) using deep Q-learning and deep deterministic policy gradient (DDPG). …”

Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

“…In CQ Routing Algorithm, the confidence value (C value) can be used to improve the quality of exploration in Q Routing Algorithm. …”
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Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network by Md Akib, Afif, Saad, Nordin, Asirvadam, Vijanth

“…A new learning algorithm called the ensemble dual algorithm for estimating the mass-flow rate of the flow after leakage is proposed. …”
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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. …”
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Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems by Mwinyi, Amir Kombo

“…To meet this requirement, a new Multi LMS (MLMS) model using Sharable Content Object Reference Model (SCORM) specifications to share learning materials among different higher learning institutions (HLIs) has been presented. …”
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A high-performance neural network algorithm using a Legendre ensemble-based extreme learning machine for solving fractional partial differential equations by Isah, Ibrahim Onimisi, Senu, Norazak, Ahmadian, Ali

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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

“…The solution provided by deep learning for a differential equation is in a closed analytical form which is differentiable and could be used in any subsequent computation. …”
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Solving the optimal path planning of a mobile robot using improved Q-learning by Low, Ee Soong, Ong, Pauline, Cheah, Kah Chun

“…In order to address this limitation, the concept of partially guided Q-learning is introduced wherein, the flower pollination algorithm (FPA) is utilized to improve the initialization of Q-learning. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…This indicates the capability of the algorithm in exploring the search space. The 2S-ENDSHHMO algorithm can be used to improve the search process of other MOSI-based algorithms and can be applied to solve MOPs in applications such as structural design and signal processing.…”
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Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting by Loh, Eng Chuen

“…Therefore, this present study had imputed the missing hydrological data using five imputation methods, namely Neural Network (NN), Moving Median (MM), Iterative Algorithm (IA), Nonlinear Iterative Partial Least Square (NIPALS), and Combined Correlation with Inversed Distance (CCID) imputation methods. …”
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Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.] by Afolabi, Akindele Segun, Akinola, Olubunmi Adewale, Odetoye, Oyinlolu Ayomidotun, Adetiba, Emmanuel

“…Furthermore, it is necessary to develop models that are robust enough to achieve acceptable performance in situations where partial data from sensors are available. In this paper, we experimentally determined the Machine Learning (ML) models that are most robust for use in indoor occupancy detection. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Thus, using neural network-based semi-supervised stream data learning is inadequate due to capture the changes in the distribution and characteristics of various classes of data while avoiding the effect of the outdated stored knowledge in neural networks (NN). …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

“…Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. A modified initialization scheme that leverages grid partitioning and oppositional-based learning is incorporated to produce an evenly distributed initial population across P-V curve. …”

Non-Distortion-Specific No-Reference Image Quality Assessment:A Survey by Abdul Manap, Redzuan, Shao, Ling

“…Over the last two decades,there has been a surge of interest in the research of image quality assessment due to its wide applicability to many domains.In general,the aim of image quality assessment algorithms is to evaluate the perceptual quality of an image using an objective index which should be highly consistent with the human subjective index.The objective image quality assessment algorithms can be classified into three main classes: full-reference,reduced-reference,and no-reference.While full-reference and reduced-reference algorithms require full information or partial information of the reference image respectively,no reference information is required for no-reference algorithms.Consequently,a no-reference (or blind) image quality assessment algorithm is highly preferred in cases where the availability of any reference information is implausible.In this paper,a survey of the recent no-reference image quality algorithms,specifically for non-distortion-specific cases,is provided in the first half of this paper.Two major approaches in designing the non-distortion-specific no-reference algorithms,namely natural scene statistics-based and learning-based,are studied.In the second half of this paper,their performance and limitations are discussed before current research trends addressing the limitations are presented.Finally,possible future research directions are proposed towards the end of this paper.…”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

“…Then, the weights are used together with either Principal Component Analysis (PCA) or Partial Least Square (PLS) to tackle the collinearity among variables. …”
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Community-based mosquito surveillance: an automatic mosquito-on-human-skin recognition system with a deep learning algorithm by Ong, Song-Quan, Gomesh Nair, Umi Kalsom Yusof, Hamdan Ahmad

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Analysis & design low power multiplier using TSMC 0.18µm CMOS technology by Norsaifulrudin Mat Zuki

“…Low power multipliers are developed through minimizing switching activities of partial product using the radix 4 booth algorithm. …”
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Evaluating the performances of Dice, Jaccard, Overlap, and Cosine coefficients in automated marking of algebraic equations / Hasnah Yusof, Wan Rolini Wan Yusoff and Masita Jamal by Yusof, Hasnah, Wan Yusoff, Wan Rolini, Jamal, Masita

“…Data was obtained from the solutions to 4 simple algebraic equations given by 180 Universiti Teknologi MARA students of different programmes within the Shah Alam campus. The algorithm used in the automated marking was adjusted to fit the DJOC coefficients. …”
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