A PARALLEL AND DISTRIBUTED FRAMEWORK FOR IMPLEMENTING BACK PROPAGATION ALGORITHM IN BIG DATA by unknown

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Automating UML Models Refactoring using Search-Based Algorithms by unknown

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A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

“…The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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Information warfare recovery-fighting back through the matrix. (c2012) by Zbib, Mirna

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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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Modeling and Control of a Robot Based Rehabilitation System for the Head-Neck Joint by Raslan, Ismail Tareq

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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

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Incremental and Heuristic Algorithms for Deriving Adaptive Distinguishing Test Cases for Nondeterministic Finite State Machines by Saleh, Ayat

Subjects: “…Model Based Testing…”
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A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System by Ameema Zainab (16864263)

Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

Particle swarm optimization based algorithm for protein structure prediction in the 3D HP model. (c2008) by Kanj, Fatima Hassan

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Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study by Mutasim Baba, Fuad

“…This methodology includes a variance-based sensitivity analysis to determine building parameters that significantly influence indoor air temperatures, the Multi-Objective Genetic Algorithm to calibrate different rooms simultaneously based on the significant param eters identified by the sensitivity analysis, and new evaluation criteria to achieve a high-accuracy calibrated model. …”
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A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

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A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks by Umesh Kumar Lilhore (17727684)

“…The proposed model also utilized an enhanced back propagation neural network for data fusion operation, which is based on multi-hop system and also operates a highly optimized momentum technique, which helps to choose only optimum energy nodes and avoid duplicate selections that help to improve the overall energy and further reduce the quantity of data transmission. …”

Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

“…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
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An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling by ALKETBI, SAIF

“…Several nonlinear optimization models were developed for this purpose assuming uniform resource availability and sequence based project tasks. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars by Abathar Al-Hamrani (16494884)

“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V_pred/V_exp) ratio of 0.97 and a coefficient of variation of 17.91%.…”