Search Results - (( developing code optimization algorithm ) OR ( learning object optimization algorithm ))

Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

Efficient Malware Detection And Response Model Using Enhanced Parallel Deep Learning (EPDL-MDR) by Chowdhury Sajadul Islam

“…The hyperparameter optimization achieved best performance by implementing the EHS algorithm at the system level, thereby increasing feature-detection accuracy and bridging the gap between deep learning innovation and real-world malware detection and response models. …”

Applying case reuse and Rule-Based Reasoning (RBR) in object-oriented application framework documentation: Analysis and design by Jani H.M., Lee S.P.

“…The main objective of an object-oriented application framework is to promote the reuse of both design and code in the development of new applications. …”

Pseudo Randomized Search Strategy (PRSS*) of the ambiguity function mapping by Hassan, Azmi

“…A combination between three methods of optimization, global random search and ambiguity function mapping produced an efficient search algorithm what the author called the Pseudo Randomized Search Strategy (PRSS). …”
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Blood cell classification using deep learning by Liaw, Mun Kin

“…The motivation was gotten from the literature review section where various researchers developed their own methods manually through experimenting such as ensemble methods, learning algorithms, combined methodologies, etc. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Proactive thermal management of photovoltaic systems using nanofluid cooling and advanced machine learning models by Masalha, Ismail, Alahmer, Ali, Badran, Omar, Al-Khawaldeh, Mustafa Awwad, Masuri, Siti Ujila, Maaitah, Hussein

“…The primary objective is to enhance PV system performance and support intelligent decision-making in renewable energy applications. …”
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Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication by JAM'AAH, SUUD

“…The initial investigation on the existing LDPC code decoding algorithms assists to develop a low complexity LDPC code decoding algorithm. …”
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Study of optimal EG placement in radial distribution system using real coded genetic algorithm by M. H., Sulaiman, Omar, Aliman

“…This paper proposes a study of embedded generation (EG) placement in radial distribution system by utilizing real coded genetic algorithm (RCGA) technique. Several cases of EG models placements are studied in order to minimize the total power losses and to improve voltage profiles of the system. …”
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Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

“…Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

“…The current major existing multi-objective recommendation approaches utilize collaborative filtering method as rating predictor to replenish the missing ratings and combined with evolutionary algorithm for only bi-objective optimization. …”
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Opposition-based learning simulated kalman filter for Numerical optimization problems by Mohd Falfazli, Mat Jusof

“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…There are three objectives in this research. The first objective is to study the effects of varying the architecture designs and parameter values of the backpropagation neural network (BPNN) learning algorithm. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

“…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Investigation on pattern based Algorithm for division by a constant number using Verilog code for optimization on the Nelust results by Fouziah Md Yassin, Ag Asri Ag Ibrahim, Zaturrawiah Ali Omar, Saturi Baco

“…One of the alternatives is by replacing it with cheaper adder and shifter to compute the same result. The research is to develop an algorithm of unsigned constant division via add-shift method using Verilog code. …”
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Multi-objective deep reinforcement learning for recommendation systems by Keat, Ee Yeo, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…However, other non-accuracy metrics such as novelty and diversity should not be overlooked. Existing multi-objective (MO) RSs employed collaborative filtering and combined with evolutionary algorithms to handle bi-objective optimization. …”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms by Almubaidin M.A., Ahmed A.N., Sidek L.M., AL-Assifeh K.A.H., El-Shafie A.

“…This involves their application to various facets of the reservoir operating system, particularly in determining optimal rule curves. This study delves into the exploration of different algorithms, including Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), Invasive Weed Optimization (IWO), Teaching Learning-Based Optimization (TLBO), and Harmony Search (HS). …”

Hyperparameter tuning in deep learning using NSGA-III: a Multi-Objective perspective by Mohamad Rom, Abdul Rahman

“…The proposed Multi-Objective NSGAIII-DL framework is benchmarked against six baseline optimization strategies—manual search, grid search, random search, Bayesian optimization, particle swarm optimization, and standard genetic algorithms using MNIST and CIFAR-10 datasets. …”
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