Search Results - (( model implication based algorithm ) OR ( based optimization based algorithm ))

A Constraint Programming-based Genetic Algorithm (CPGA) for Capacity Output Optimization by Ean, Kate Nee Goh, Jeng, Feng Chin, Wei, Ping Loh, Chea, Ling Tan

“…Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company. …”
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Agreement options for negotiation on material location decision of housing development by Utomo, C., Rahmawati, Y.

“…Decision algorithms are based on the cooperative game theory to develop the agreement options and coalition formation. …”
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Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

“…The primary objectives were to assess the performance of three evolutionary algorithms ? Heap-Based Optimizer (HBO), Multiverse Optimizer (MVO), and Whale Optimization Algorithm (WOA) ? …”

Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai, V., Ahmed, Ali Najah, Malek, Marlinda Abdul, El-Shafie, Ahmed, El-Shafie, Amr

“…GP is a meta-heuristic search and optimization technique based on natural evolution. The control and optimization parameters in this study are tuned. …”
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A hybrid deep learning-based unsupervised anomaly detection in high dimensional data by Muneer, A., Taib, S.M., Fati, S.M., Balogun, A.O., Aziz, I.A.

“…However, Adamax optimization algorithm showed the best results when employed to train the DANN model. …”
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Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods by Salih, Rawia Tahrir

“…The evaluation criteria of Many Objective Optimization algorithm (MaOO) play a critical role in evaluating the competition MaOO algorithms. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Predicting the classification of heart failure patients using optimized machine learning algorithms by Ahmed, Marzia, Mohd Herwan, Sulaiman, Hassan, Md Maruf, Bhuiyan, Touhid

“…Model selection was further refined using information criteria, including Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), ensuring that the best-performing model was chosen based on both predictive accuracy and model complexity. …”
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A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection by Basheer G.S., Ahmad M.S., Tang A.Y.C.

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Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai V., Ahmed A.N., Malek M.A., El-Shafie A., El-Shafie A.

“…GP is a meta-heuristic search and optimization technique based on natural evolution. The control and optimization parameters in this study are tuned. …”

Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…Practical implications In terms of managerial implications, the findings in this research help to frame the adoption of a more advanced analytical approach to forecasting, using a Machine Learning algorithm, in solving a newsvendor problem. …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…Overall, this thesis presents five contributions: the proposed modified word vectors algorithm, the new contextual classification dataset named QCoC, the efficient question-type classifier based on the feed-forward neural network algorithm, the potential transferability of the presented work to other domains, and the practical implications of the presented work towards cases where computational resources are limited or costly.…”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

“…The paper suggests that the ARIMA technique offers practical implications for market analysts, enabling them to make well-informed decisions based on accurate price projections. …”
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Prediction of payment method in convenience stores using machine learning by Pratondo, Agus, Novianty, Astri, Pudjoatmodjo, Bambang

“…The high accuracy rate suggests that machine learning models can effectively assist in tailoring services and marketing strategies based on predicted payment preferences.…”
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Optimization of hybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization by Siti Nurhazwani Husna, Mohd Hata, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation. The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi Objectives Evolutionary Algorithm Based on Decomposition, the Multi Objectives Particle Swarm Optimization, and the recent algorithm Multi Objectives Grey Wolf Optimizer. …”
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Optimization ofhybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization by Siti Nurhazwani Husna, Mohd Hata, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…A case study was conducted using fourteen jobs across three stages, which involved the use oflathes, millingmachines, and deburring machines. The EE-HFS was optimized using Multi-Objective Tiki Taka Optimization (MOTTA).The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation.The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi-ObjectiveEvolutionary Algorithm Based on Decomposition, the Multi-ObjectiveParticle Swarm Optimization,and the recent algorithm,the Multi-ObjectiveGrey Wolf Optimizer. …”
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Optimal design of low-voltage distribution networks for CO2 emission minimisation. Part II: Discrete optimisation of radial networks and comparison with alternative design strategi... by Gan, Chin Kim

“…This study extends the model for optimal environmental design of distribution systems presented in Part I to network analyses. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Web-based marketing communication to develop brand image and brand equity of higher educational institutions: a structural equation modelling approach by Momen, Md. Abdul, Sultana, Seyama, Haque, A. K. M. Ahasanul

“…However, configuring the right mix in the age of social networking sites and various online displays and constantly changing algorithm in search engine optimization have become major challenges today. …”
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