Search Results - (( model evaluation from algorithm ) OR ( whale classification system algorithm ))

Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

“…Selecting the relevant features from the data leads to better classification results. Optimization algorithms are successfully applied in the feature selection task in many systems. …”
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Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

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Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition by Muhammad Arif, Mohamad, Jamaludin, Sallim, Kohbalan, Moorthy

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Hybrid binary whale with harris hawks for feature selection by Alwajih, R., Abdulkadir, S.J., Al Hussian, H., Aziz, N., Al-Tashi, Q., Mirjalili, S., Alqushaibi, A.

“…This study introduces the BWOAHHO memetic technique, which combines the binary hybrid Whale Optimization Algorithm (WOA) with Harris Hawks Optimization (HHO). …”
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Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification by Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

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Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment by Ahmed Hamza, Manar, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, S. Alotaibi, Saud, Mahgoub, Hany, S. Mehanna, Amal, Motwakel, Abdelwahed

“…Finally, MVO algorithm is exploited with Bidirectional Gated Recurrent Unit (BiGRU) model for classification. …”
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MRI brain tumor detection methods using contourlet transform based on time adaptive self-organizing map by Ali Farzamnia, Seyed Hamidreza Hazaveh, Seyede Safieh Siadat, Ervin Gubin Moung

“…Our method is compared to other methods used in past research and shows promising results for the precise classification of MRI brain images. Through conducting experiments on different test samples, our system has successfully attained a classification accuracy exceeding 98.5%. …”
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Hybrid feature selection of microarray prostate cancer diagnostic system by Mohd Ali, Nursabillilah, Hanafi, Ainain Nur, Karis, Mohd Safirin, Shamsudin, Nur Hazahsha, Shair, Ezreen Farina, Abdul Aziz, Nor Hidayati

“…This work proposes a new hybrid feature selection method, namely the relief-F (RF)-genetic algorithm (GA) with support vector machine (SVM) classification method. …”
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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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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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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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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

“…Therefore, this study focused to contribute on evaluating different algorithm models such as traditional ML and deep learning models with big stock data of multiple parameters from selected companies in Bursa Malaysia. …”

Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M.

“…This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala's, Acir's, Liu's, and Dingle's peak models. …”
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Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network by Asrul, Adam, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai, Marizan, Mubin

“…This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala’s, Acir’s, Liu’s, and Dingle’s peak models. …”
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Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH by Siti Roslindar, Yaziz, Roslinazairimah, Zakaria

“…The study of the multistep ahead forecast is significant for practical application purposes using the proposed statistical model. This study is proposing a new algorithm of Box-Jenkins and GARCH (or BJ-G) in evaluating the multistep forecasting performance of the BJ-G model for highly volatile time series data. …”
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An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance by Raheem, Ajiboye Adeleke

“…Also, for a more efficient exploration of students‟ data collected for this research, a Rule-Based Algorithm is proposed and implemented. The predictive models emanated from the two approaches were evaluated in order to validate their effectiveness. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

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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Agent-based extraction algorithm for computational problem solving by Rajabi, Maryam

“…How far the proposed agent-based model for CPS is able to help novice programmer is evaluated by conducting a group based experiment with 35 students from Faculty of Computer Science and Information Technology (FSKTM). …”
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Performance evaluation of state-of-the-art 2D face recognition algorithms on real and synthetic masked face datasets by Khan, Mohammad Amir, Faizabadi, Ahmed Rimaz, Rashid, Muhammad Mahbubur, Zaki, Hasan Firdous

“…On a larger-scale dataset MLFW, the impact of mask-wearing on FR models was also up to 50%. We trained and evaluated a proposed Mask Face Recognition (MFR) model whose performance is much better than the SOTA algorithms. …”
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