Search Results - (( model validation mead algorithm ) OR ( level classification _ algorithm ))

Optimizing the SEIRD model for COVID-19 in Malaysia using pymoo framework by Abdul Hadi, Muhammad Salihi, Amran, Muhammad Aiman Haziqh, Zulkarnain, Norsyahidah

“…To solve this, the Nelder-Mead and Pattern Search algorithms were recommended. …”
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Wastewater treatment process: a modified model for oxidation pond by Syafiqah Hanis, Mohd Fauzi

“…The model has been solved numerically by using the 4th order Runge-Kutta method and a parameter fitting technique namely Nelder-Mead simplex algorithm embedded in MATLAB software. …”
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Mathematical modelling of covid-19 transmission and vaccine effectiveness for a university by Shahirah Atikah, Mohamad Husnin

“…The models were numerically solved using the Runge Kutta fourth order method (RK4) and parameter fitting techniques namely Pattern Search and Nelder-Mead Simplex algorithm embedded in MATLAB software. …”
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Simulation of COVID-19 outbreaks via graphical user interface (GUI) by Mohd Jamil, Norazaliza, Rosli, Norhayati, Muhammad, Noryanti

“…Background: This research aimed to model the outbreak of COVID-19 in Malaysia and develop a GUI-based model. …”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

“…The results of the experiments show that the MCML classification algorithm successfully performs detailed classification and produces promising results for each classification level. …”
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Symmetric Key Size for Different Level of Information Classification by Ibrahim, Subariah, Maarof, Mohd. Aizaini

“…Confidential information can be categorized into various levels of classification. The classification depends on the level of damage to an organization or to national security when the information is disclosed. …”
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Mathematical model for predicting the performance of photovoltaic system with delayed solar irradiance by Siti Nurashiken, Md Sabudin

“…The numerical solution is obtained by adopting the Runge Kutta method coupled with a parameter fitting technique, the Nelder Mead algorithm, which is implemented by using MATLAB software. …”
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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 numerical solution is obtained by adopting the 4th-order Runge Kutta method coupled with a parameter fitting technique, the Nelder Mead algorithm, which is implemented by using MATLAB software. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…Classification (of information); Learning algorithms; Students; Class imbalance; Data level; Over sampling; Performance prediction; SMOTE; Spread subsampling; Student performance; Student performance prediction; Under-sampling; Machine learning…”

Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

“…This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.…”
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Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

“…These features have been exploited in different algorithms for automatic classification of medical X-ray images. …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

“…The ZeroR algorithm was set as the baseline There are three levels of classification analyses: before and after handling the missing values, before and after the outliers’ treatment, and adding uncertain classes. …”
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Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study by Sim, Doreen Ying Ying, Teh, Chee Siong, Ahmad Izuanuddin, Ismail

“…Prediction and/or classification accuracies of cfsw-SVM algorithms are significantly improved.…”
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Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…Chi-square, a filter method that is computationally fast, simple and has the ability to deal with a large dimensional feature, is used as the first level of the feature selection process. After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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Multilayer Perceptron Neural Network In Classifying Gender Using Fingerprint Global Level Features by Siti Fairuz, Abdullah, Ahmad Fadzli Nizam, Abdul Rahman, Zuraida, Abal Abas, Wira Hidayat, Mohd Saad

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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…However, there is a need to explore more algorithms that can yield better classification performance. …”
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Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

“…The low-level features such as edges, blobs, and ridges were extracted for grouping and classification. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Additionally, the traffic are relying on the markers and scheduling algorithms to the service classes at the routers. The higher level priority agreements give a higher or equal probability than the lower level, this technique is perfect at a core router by scheduling algorithm. …”
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An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab by Bassam Ali Qasem, Al-Qatab

“…Firstly, intra-severity classification intended to identify the level of severity of the dysarthric speakers. …”
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