Search Results - (( data optimization model algorithm ) OR ( data implication _ algorithm ))
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Modelling of heuristic distribution algorithm to optimize flexible production scheduling in Indian industry
Published 2020“…Therefore, the optimized error of 0.456 than the mathematical data and hence, this model is validated.…”
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A hybrid deep learning-based unsupervised anomaly detection in high dimensional data
Published 2022“…However, Adamax optimization algorithm showed the best results when employed to train the DANN model. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…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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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The best algorithm will not be the same for all the data sets. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
Published 2024journal::journal article -
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…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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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions
Published 2023“…Moreover, the research experiments are repeated several times to achieve the best results by employing hyperparameter tuning of each algorithm. This involves selecting an appropriate kernel and suitable data normalization technique for SVR, determining ARIMA's (p, d, q) values, and optimizing the loss function values, number of neurons, hidden layers, and epochs in LSTM models. …”
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Agreement options for negotiation on material location decision of housing development
Published 2020“…Social implications: The satisficing algorithm of the coalition will satisfy all stakeholders. …”
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Prediction of payment method in convenience stores using machine learning
Published 2023“…The dataset used in this study was collected from a diverse sample of the Indonesian population, reflecting the multifaceted nature of payment behaviors in the region. The Random Forest algorithm was employed due to its robustness in handling complex, high-dimensional data, and its ability to provide reliable predictions. …”
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Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model
Published 2017“…The present results have wider implications not only for streamflow forecasting purposes, but also for other hydro-meteorological forecasting variables requiring only the historical data input data, and attaining a greater level of predictive accuracy with the incorporation of the FFA algorithm as an optimization tool in an ANFIS model.…”
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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
Published 2025“…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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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…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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Thesis -
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Model for responsive agriculture hub via e-commerce to sustain food security
Published 2024“…The model integrates data-driven decision-making, supply chain optimization, and digital marketplaces to enhance the efficiency and resilience of agricultural systems. …”
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Short-Term forecasting of floating photovoltaic power generation using machine learning models
Published 2024“…The results indicate that the Neural Networks model consistently outperforms the other machine learning algorithms in terms of predictive accuracy. …”
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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...
Published 2022“…Because of their effectiveness in identifying geologic features, seismic attributes are usually used as input to machine learning (ML) models for facies classification. Typically, too many attributes are computed for facies classification, making a predictive modeling task more challenging. …”
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Development of decentralized data fusion algorithm with optimized kalman filter.
Published 2016“…This thesis proposes a data fusion model that facilitates selection of algorithm and recommends selected algorithm to be optimized. …”
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Thesis -
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems
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Working Paper
