Search Results - (( wolf optimization bat algorithm ) OR ( based observational risk algorithm ))

Metaheuristic Algorithms and Neural Networks in Hydrology

“…It starts with the introduction of ANNs as a black box model, followed by the coupling of various metaheuristic algorithms with ANNs to form novel neural network models for solving real-world problems in hydrology, including Particle Swarm Optimization (PSO) for rainfall-runoff modeling, Bat Optimization (Bat) and Cuckoo Search Optimization (CSO) for future rainfall prediction, the Whale Optimization Algorithm (WOA) and Salp Swarm Optimization (SSO) for future water level prediction, Grey Wolf Optimization (GWO), Multi-Verse Optimization (MVO), the Sine Cosine Algorithm (SCA) and the Hybrid Sine Cosine and Fitness Dependent Optimizer (SC-FDO) for imputing missing rainfall data.…”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

“…In this paper, the status of MOO research and state-of-the-art MOSI algorithms namely, multi-objective particle swarm, artificial bee colony, firefly algorithm, bat algorithm, gravitational search algorithm, grey wolf optimizer, bacterial foraging and moth-flame optimization algorithms have been reviewed. …”
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Task scheduling in cloud computing using Harris-Hawk Optimization by Iza A. A. Bahar, Azali Saudi, Abdul Kadir, Syed Nasirin Syed Zainol Abidin, Tamrin Amboala, Esmadi Abu Bin Abu, Abdullah B. Mohd. Tahir, Suddin Lada

“…In this study, the proposed HHO algorithm is simulated and compared with other well-known swarm intelligence algorithms, including Bat Algorithm (BA), Grey Wolf Optimization (GWO), and Particle Swarm Optimization (PSO). …”
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A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation by Mohd Yusof, Norfadzlia, Muda, Azah Kamilah, Pratama, Satrya Fajri, Abraham, Ajith

“…In addition, statistical significance tests are also conducted using the Friedman test and Wilcoxon signed-rank test. The comparative optimization algorithms include two BWOA variants, binary bat algorithm (BBA), binary gray wolf algorithm (BGWOA), and binary manta-ray foraging algorithm (BMRFO). …”
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Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

“…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

“…Extensive studies prove the proposed algorithm outperforms bat algorithm (BA), improved grey wolf optimizer (IGWO), conventional PSO and P&O, with convergence time shorter than 0.3 s and tracking accuracy above 99% under different complex PSCs. � 2010-2012 IEEE.…”

Adaptive Switching Gravitational Search Algorithm: An Attempt To Improve Diversity Of Gravitational Search Algorithm Through Its Iteration Strategy by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Marizan, Mubin, Shahdan, Sudin

“…The proposed ASw-GSA is also compared to original GSA, particle swarm optimization (PSO), genetic algorithm (GA), bat-inspired algorithm (BA) and grey wolf optimizer (GWO). …”
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Performance comparison of different swarm intelligence methods towards benchmark functions by Song, Wen Huan

“…The original version of PSO, Inertia Weight PSO (IWPSO), Linearly Decrease Inertia Weight PSO (LDIW-PSO), Random Inertia Weight PSO (RIW-PSO), Constriction Factor PSO (CF-PSO) along with and without velocity clamping (VC) are analyzed and compared with Grey Wolf Optimizer (GWO) and Bat Algorithm (BA). The performance of SI method is tested using ten benchmark functions. …”
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Machine learning-based risk prediction model for medication administration errors in neonatal intensive care units: a prospective direct observational study by Henry Basil, Josephine, Lim, Wern Han, Syed Ahmad, Sharifah M., Menon Premakumar, Chandini, Mohd Tahir, Nurul Ain, Mhd Ali, Adliah, Seman, Zamtira, Ishak, Shareena, Mohamed Shah, Noraida

“…Each observation was independently assessed for errors. Ten machine learning (ML) algorithms were applied with features derived from systematic reviews, incident reports, and expert consensus. …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

“…The results obtained from the proposed meta-heuristic algorithms of this study were then evaluated for reservoir risk analysis, for the observed period assessment and the climate assessment. …”
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Risk perception modeling based on physiological and emotional responses / Ding Huizhe by Ding , Huizhe

“…The ANN demonstrated superior ability in distinguishing low and high-risk levels. However, when risk degrees were closely matched, the integrated model with weight adjustments based on base models outperformed ANN. …”
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Modeling Earthquake Bond Prices with Correlated Dual Trigger Indices and the Approximate Solution Using the Monte Carlo Algorithm by Riza Andrian Ibrahim, Sukono, Herlina Napitupulu, Rose Irnawaty Ibrahim

Routine insulin sliding scale protocol versus software driven algorithm (star protocol) for blood glucose management of critically ill patients in the ICU: A prospective observatio... by Tan, Ru Yi

“…This was a prospective observational study conducted over a duration of 1 year. …”
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Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

“…In this thesis the analysis of this particular model was based on the cause-specific hazard of Cox model. …”
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Risk assessment of dengue in Betong Sarawak using simple mathematical model by Gunap, Timothy

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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

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Steady state security analysis using artificial neural network by Mohd Nor, Nurul Huda

“…The cases where operating violations are observed are considered as alert , while the cases for which the load flow algorithm exhibits a diverging algorithmically solution, are considered as emergency. …”
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Prediction of Heart Disease Risk Using Machine Learning with Correlation-based Feature Selection and Optimization Techniques by Reddy, K.V.V., Elamvazuthi, I., Aziz, A.A., Paramasivam, S., Chua, H.N., Pranavanand, S.

“…The Optimizable k-Nearest Neighbors algorithm achieved an utmost accuracy of 95.04, area under the ROC curve of 0.99 on the Correlation-based Feature Selection optimal set, and that of 90.34, 0.96 respectively, on full features. …”
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Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection by Siti, Mujilahwati, Noor Zuraidin, Mohd Safar, Ku Muhammad Naim, Ku Khalif, Nasyitah, Ghazalli

“…This study examines the optimization of Indonesian text sentiment analysis through the integration of feature selection using a genetic algorithm (GA) with deep learning models. The application of GA for data dimensionality reduction from 41,140 to 20,769 features, coupled with fitness evaluation based on SVM, resulted in an observed increase in accuracy by 8.10% for SVM, 36.1% for Naïve Bayes, 7.82% for LSTM, 5.47% for DNN, and 6.25% for CNN. …”
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Radiation dose, cancer risk and diagnostic performance of computed tomography pulmonary angiography examination by Haspi Harun, Hanif

“…CNR and FOM performed significantly better when IR algorithm levels were increased, tube potential was reduced, and if patients had smaller body sizes (p < 0.05) while fluctuation trends were observed in SNR. …”
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