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Optimized controllers for stabilizing the frequency changes in hybrid wind-photovoltaic-wave energy-based maritime microgrid systems by Peddakapu, K., Mohd Rusllim, Mohamed, Srinivasarao, P., Licari, J.

“…The AOA-based 2DOF-TIDN performance is compared to the following algorithms: genetic, Jaya, bat, grasshopper optimization, particle swarm optimization, and moth flame optimization. …”
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Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin

“…The fuzzy models are trained applying locally linear model tree algorithm followed by a meta-heuristic nature inspired algorithm called bat algorithm. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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Development of near-sea-level Langley calibration algorithm for aerosol optical depth measurement by Chang, Jackson Hian Wui

“…The consistency of the proposed method is also validated with good resultsover two study areas (n=241) with different location, day, and time. …”
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Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0 by Chong, Agnes Wen Lin

“…In this project, Fornell-Larker parameters are used to test the measurement algorithm for the research's discriminant validity. 380 valid questionnaires returnedback and conducted the calculation of the algorithm's assessment to constructs' validity and realibility assessment, discriminant validity using HTMTand Fornell-Larker approaches. …”
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Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz by Muhammad Firdaus , Aziz

“…TIMI risk score reported lower performance for STEMI (In-hospital: AUC=0.81, 30 days: AUC=0.80 and 1-year: AUC=0.76) and NSTEMI/UA patients (In-hospital: AUC=0.42, 30 days: AUC=0.49 and 1- year: AUC=0.42) as compared to ML and DL algorithms. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

“…Validation of the best ML model was performed against Thrombolysis in Myocardial Infarction (TIMI) using an additional dataset of 102 patients. …”
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Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques by Googhari, Shahram Karimi

“…For validation and testing, all performance indices of selected ANFIS model were inferior to those of the ANN model. …”
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Multi-objective genetic algorithm driven formulation of a plant-based probiotic premix powder: Nutrient-cost modeling, microstructural characterization and sensory validation by Tang, Ping, Cui, Ming Yang, Mohsin, Aliah Zannierah, Meor Hussin, Anis Shobirin, Juhari, Nurul Hanisah

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Mathematical model for predicting the performance of photovoltaic system with delayed solar irradiance by Siti Nurashiken, Md Sabudin

“…The simulation study is carried out for the three scenarios of weather conditions: a clear day, a slightly cloudy day, and a heavily overcast day. …”
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Mathematical model for predicting the performance of photovoltaic system with delayed solar irradiance by Siti Nurashiken, Md Sabudin, Norazaliza, Mohd Jamil

“…The simulation study is carried out for the three scenarios of weather conditions: a clear day, a slightly cloudy day, and a heavily overcast day. …”
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Personalized Prediction Clothing Algorithm Based on Multi-modal Feature Fusion by Rong, Liu

“…To assess the generalization ability of the two models, cross-validation was performed. The experimental results indicate that the 1DCNN-2DCNN model exhibits superior generalization, achieving a recall rate of 97.20%, an F1 score of 98.60%, a macro average of 98.62%, a weighted average of 98.63%, and model accuracy of 98.59%. …”
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Computationally efficient single layer transformer convolutional encoder for accurate price prediction of agriculture commodities by Bundak, Caceja Elyca, Abd Rahman, Mohd Amiruddin, Mohd Haniff, Nurin Syazwina, Afrizal, Nur Syaiful, Yusof, Khairul Adib, Abdul Karim, Muhammad Khalis, Mamat, Md Shuhazlly, Rahmat, Romi Fadillah

“…This study focuses on various vegetable prices, such as tomatoes, long beans, and cucumbers, with empirical validation across various prediction prices, specifically 30-day, 60-day, and 90-day predictions. …”
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Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution by Mohammed, Mazin Abed, Abd Ghani, Mohd Khanapi, Hamed, Raed Ibraheem, A. Mostafa, Salama, Ahmed Ibrahim, Dheyaa, Jameel, Humam Khaled, Alallah, Ahmed Hamed

“…For the purpose of testing the algorithm’s capability and reliability, it was applied to solve the same problem online validated and it achieved success in finding a shorter route. …”
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Application of artificial neural network to simulate phenolic content and antioxidant activity during spontaneous fermentation of Carica papaya leaf / Nur Syahira Mohammad and Moha... by Mohammad, Nur Syahira, So’aib, Mohamad Sufian

“…Data used to derive and validate the model was obtained from the experiment. …”
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Vehicular traffic noise prediction and propagation modelling using artificial neural network by Ahmed, Ahmed Abdulkareem

“…The model also outperforms the Multilayer Perceptron (MLP) model by almost 5% of validation accuracy and 0.3 dB in noise level prediction. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…The main challenge in this area is providing highly accurate and efficient day-ahead price forecasting. A suitable feature selection technique, which is able to model the interacting features and nonlinearities of the forecast processes, is still required although researches have been performed for day-ahead forecasting. …”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

“…Accuracy and efficiency of the day-ahead price forecasting process are complex challenges in deregulated electricity market. …”
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Prediction of epidemic peak and infected cases for COVID-19 disease in Malaysia, 2020 by Alsayed A., Sadir H., Kamil R., Sari H.

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.

“…For the model validation, we utilize widely used evaluation techniques: Mean Absolute Error, Root Mean Squared Error, Mean Absolute Percentage Error, and R-squared. …”
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