Search Results - predicting low difference ((optimisation algorithm) OR (optimization algorithm))
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Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm
Published 2025“…The focus of this study is to determine the optimum input parameter of the 3D printer using the Bees Algorithm (BA). This study uses the Bees Algorithm to predict the best combination parameters to optimise the surface roughness of parts printed by a fused deposition modelling (FDM) machine. …”
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Book Chapter -
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Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab
Published 2025“…The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
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Thesis -
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Enhancing NoC-based MPSoC performance: a predictive approach with ANN and guaranteed convergence arithmetic optimization algorithm
Published 2023“…The main idea of the proposed method is to develop a prediction model, speci‚cally an Arti‚cial Neural Network (ANN) optimized using the Guaranteed Convergence Arithmetic Optimization Algorithm (GCAOA-ANN), for predicting the utilized routing algorithm in NoC-based MPSoC platform during the DSE process. …”
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Predicting heart disease using ant colony optimization / Siti Aisyah Ismail
Published 2021“…Thus, this study used the Ant Colony Optimization algorithm with data mining called Ant-Miner to predict heart disease because it is said that Ant-Miner’s rule list is simpler than other rule induction algorithms. …”
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Student Project -
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Hybrid Sine Cosine and Fitness Dependent Optimizer for global optimization
Published 2021“…To optimize the performance, FDO calculates velocity (pace) differently. …”
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Prediction of optimum compositions of parenteral nanoemulsion system loaded with low solubility drug for treatment of schizophrenia by artificial neural network
Published 2016“…It was found that the optimal algorithm and topology were the quick propagation and the configuration with 5 inputs, 4 hidden and 1 output nodes, respectively. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms
Published 2017“…The absolute range of residual errors (e) was very low less than 10 to indicate that the surface roughness could be accurately predicted by the model. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification
Published 2024“…However, compared with the traditional risk control algorithm (logistic regression algorithm), CatBoost algorithm also needs to have the advantages of high efficiency, low algorithm complexity and strong interpretable ability. …”
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NEXT-HOUR ELECTRICITY PRICE FORECASTING USING LEAST SQUARES SUPPORT VECTOR MACHINE AND GENETIC ALGORITHM
Published 2023“…Nevertheless, many existing models have relatively low prediction accuracy. Furthermore, single prediction models are typically less accurate for different scenarios. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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Temporal integration based factorization to improve prediction accuracy of collaborative filtering
Published 2016“…The TemporalMF++ approach relies on the k-means algorithm and the bacterial foraging optimization algorithm. …”
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An efficient model for indoor radio signal prediction and coverage estimation / Md. Sumon Sarker
Published 2011“…And the second algorithm is the optimization technique for indoor wireless coverage. …”
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Biochar production from valorization of agricultural Wastes: Data-Driven modelling using Machine learning algorithms
Published 2023“…The artificial neural network-based algorithms outperformed the SVM and GPR as indicated by the R2 > 0.9 and low predictive errors. …”
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Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction
Published 2024“…However, predicting software defects with irrelevant features and overlapping classes is challenging and can lead to lengthy training and low model accuracy. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…Only the normal traffic predicted by the ML-IDS algorithm will be allowed to enter the network domain, and the route with the fastest delay predicted by the ML-RA is assigned for routing. …”
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