Search Results - (( data optimization _ algorithm ) OR ( data implication learning algorithm ))

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

“…The best algorithm will not be the same for all the data sets. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

“…Types of attacks can be Ping of Death, flooding, remote-controlled attacks, UDP flooding, and Smurf Attacks. Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. …”
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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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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network by Hairuddin, Nurul Liyana, Yusuf, Lizawati Mi, Othman, Mohd Shahizan

“…Besides that, another limitation that exists in previous researches is the absence of parameter optimization for the classifier. Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Ahmad Salihin, Samsudin, Amir Izzani, Mohamed, Mohd Mawardi, Saari

“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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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.

“…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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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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Prediction of payment method in convenience stores using machine learning by Pratondo, Agus, Novianty, Astri, Pudjoatmodjo, Bambang

“…This study explores the application of machine learning techniques, specifically the Random Forest algorithm, to predict payment modes in the context of the Indonesian community. …”
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Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making by Chuan, Zun Liang, Chong, Teak Wei, Japashov, Nursultan, Soon, Kien Yuan, Tan, Wei Qing, Noriszura, Ismail, Liong, Choong-Yeun, Tan, Ee Hiae

“…Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Short-Term forecasting of floating photovoltaic power generation using machine learning models by Mohd Herwan, Sulaiman, Mohd Shawal, Jadin, Zuriani, Mustaffa, Mohd Nurulakla, Mohd Azlan, Hamdan, Daniyal

“…The results indicate that the Neural Networks model consistently outperforms the other machine learning algorithms in terms of predictive accuracy. …”
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Using Machine Learning to Optimize Green Influencer Marketing Strategies: A Study of Consumer Behavior Trends by Neetu, Sharma

“…In the backdrop of increasing sustainability awareness among Indian consumers, this study explores the role of machine learning (ML) in optimizing green influencer marketing strategies to drive eco-conscious purchasing. …”
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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

“…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
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Artificial intelligence (AI) and its application in architecture design: a thematic review by Jin, Deran, Zairul, Mohd, Salih, Sarah Abdulkareem

“…The analysis identified six primary themes: 1) Architecture and Science, which includes research on complex systems, genetic algorithms, and machine learning;2) Architecture and Construction Management, including the development of frameworks that support decision making; architecture and interior design, which includes work on space-planning optimization and furniture and occupant arrangement;3) Architecture Interior Design; 4) Architecture and Urban; which encompasses attempts to develop tools to help design new cities; architectural engineering, where building performance analysis was the most-common AI application; 5) Architectural Engineering; and 6) Design Education and Training, in which AI appears most promising for advancing problem-based learning. …”
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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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Evaluation of principal component analysis for reducing seismic attributes dimensions: Implication for supervised seismic facies classification of a fluvial reservoir from the Mala... by Babikir, I., Elsaadany, M., Sajid, M., Laudon, C.

“…Correlation coefficients, including Pearson, Rank, and Mutual Information (MI) that map the relationship between the input features and the 3-classes output, are calculated to select the optimal subset of features. We train and test support vector machine (SVM), random forest (RF), and neural network (NN) algorithms that are widely used in seismic facies classification. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…Thirdly, the pedestrian's behaviour is recognized using grid optimizer in machine learning. Fourthly, four standard vectors for pedestrian walking behaviour are developed. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…Thirdly, the pedestrian's behaviour is recognized using grid optimizer in machine learning. Fourthly, four standard vectors for pedestrian walking behaviour are developed. …”
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Analyzing surface settlement factors in single and twin tunnels : A review study by Huat, Chia Yu, Danial Jahed, Armaghani, Lai, Sai Hin, Hossein, Motaghedi, Panagiotis G., Asteris, Pouyan, Fakharin

“…Leveraging historical data and ML algorithms can enhance SS prediction accuracy and aid in proactive risk management. …”
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Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

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A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

“…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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