Search Results - (( model evaluation ((a algorithm) OR (_ algorithm)) ) OR ( wave optimization strategy algorithm ))

Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Computational electromagnetic modeling and optimization techniques to enhance the accuracy and efficiency of a 2.45 GHz pyramidal horn antenna by Newton-Raphson method for IEMI tes... by Hamamah, Fuad, Ahmad, Wfh F.H.W., Gomes, C., Mohd Isa, M., Homam, M. J.

“…Using CST Microwave Studio and optimization techniques, the return losses for the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Interior Point Quadratic Newton (IPQN), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) were-29.61dB,-30.45dB,-26.2dB, and-30.24dB, respectively. …”
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Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall by Mustafa, M.R., Rezaur, R.B., Saiedi, Saied, Rahardjo, H., Isa, M.H.

“…The performance of the training algorithms was evaluated using standard performance evaluation measures—root mean square error, coefficient of efficiency, and the time and number of epochs required to reach a predefined accuracy. …”
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Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting by HASSAN, SAIMA

“…The aggregation algorithms were employed on the forecasts obtained from all individual NN models as well as on a number of the best forecasts obtained from the best NN models. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary by Mohd Zamary, Nurul Aida

“…This project aims to develop a decision-making support model for diabetes diagnosis and treatment recommendation using the decision tree algorithm. …”
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Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH by Siti Roslindar, Yaziz, Roslinazairimah, Zakaria

“…Based on the empirical results, the proposed algorithm of multistep ahead forecast to the algorithm of BJ-G provides a promising procedure to assess the performance of the BJ-G model in forecasting a highly volatile time series data. …”
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Ringed seal search for global optimization via a sensitive search model / Younes Saadi by Younes, Saadi

“…The proposed algorithm is characterized by a search model namely the sensitive search model, where the exploitation-exploration is adaptively balanced. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. …”
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Real-time slicing algorithm for Stereolithography (STL) CAD model applied in additive manufacturing industry by F. A., Adnan, F. R. M., Romlay, Nasir, Shafiq

“…This paper evaluates a real-time slicing algorithm for slicing an STL formatted computer-aided design (CAD). …”
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Modelling and environmental assessment of heterogeneous catalysis biodiesel process using war algorithm by As Eleyana, Ali

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Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

“…The results of the evaluation demonstrated varying performances among the three evolutionary algorithms. …”

Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti by Abd Mokti, Nurnazifah

“…This research project focuses on developing a laptop price prediction model using the decision tree algorithm based on laptop specifications. …”
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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.

“…Furthermore, an Archimedes optimization algorithm (AOA) is used to optimize the 2DOF-TIDN controller. …”
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Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method by Mohammed, Rawia Tahrir, Yaakob, Razali, Mohd Sharef, Nurfadhlina, Abdullah, Rusli

“…This study proposed a distinct unifying model for the MaOO evaluation criteria using the fuzzy Delphi method. …”
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Evaluating machine learning algorithms for sentiment analysis: a comparative study to support data-driven decision making by Mohamad Daud, Nur Hafiza, Shafii, Nor Hayati, Md Nasir, Diana Sirmayunie, Fauzi, Nur Fatihah

“…This research investigates the accuracy and robustness of sentiment analysis models through a comparative analysis of three distinct machine learning algorithms: Bernoulli Naive Bayes, Linear Support Vector Machines, and Logistic Regression. …”
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. …”
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