Search Results - (( java application customization algorithm ) OR ( parameter intervention model algorithm ))

VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

“…It is noted that active user intervention increases the acceleration of Genetic Algorithm towards an optimal solution. …”
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Estimation of the Epidemiological Parameter for the COVID-19 Outbreak by Muhammad Fahmi, Ahmad Zuber, Norhayati, Rosli, Noryanti, Muhammad

“…Estimation of the epidemiological parameters of the SIRD model is crucial for understanding the virus's transmission and effect of the virus, thus, helping in making informed decisions about the required interventions. …”
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Epidemiological parameter estimation of sird model for covid-19 outbreak by Muhammad Fahmi, Ahmad Zuber, Norhayati, Rosli, Noryanti, Muhammad

“…This paper is devoted to the parameter estimation of the SIRD model using the Markov Chain Monte Carlo (MCMC) method of the Metropolis Hasting algorithm. …”
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Golden exponential smoothing: a self-adjusted method for identifying optimum alpha / Foo Fong Yeng, Azrina Suhaimi and Soo Kum Yoke by Yeng, Foo Fong, Suhaimi, Azrina, Yoke, Soo Kum

“…The findings show that the GES model is self-adjusted according to the situation and converged fast in the algorithm training process. …”
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Mathematical modelling of covid-19 transmission and vaccine effectiveness for a university by Shahirah Atikah, Mohamad Husnin

“…Then, the model's complexity was increased to Model II, utilizing the time-dependent epidemiological parameters. …”
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Performance of hybrid GANN in comparison with other standalone models on dengue outbreak prediction by Husin, Nor Azura, Mustapha, Norwati, Sulaiman, Md. Nasir, Yaacob, Razali, Hamdan, Hazlina, Hussin, Masnida

“…The result showed that neighboring location of dengue cases was very effective in predicting the dengue outbreak and it is proven that the hybrid Genetic Algorithm and Neural Network (GANN) model significantly outperforms standalone models namely regression and Neural Network (NN).…”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…Predicting reservoir water level is complex because it depends on factors such as climate parameters and human intervention. Therefore, predicting water level needs robust models. …”

Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Hand, Foot and Mouth Disease (HFMD)'s Hotspot Identification using Bipartite Network Model by Nor Shamira, Sabri

“…The location nodes in the targeted and validated models were ranked using the web-based search algorithms according to the respective ranking values. …”
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Simulation of COVID-19 outbreaks via graphical user interface (GUI) by Mohd Jamil, Norazaliza, Rosli, Norhayati, Muhammad, Noryanti

“…An improved SIRD model was solved via the 4th order Runge-Kutta (RK4) method and 14 unknown parameters were estimated by using Nelder- Mead algorithm and pattern-search technique. …”
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A fast learning network with improved particle swarm optimization for intrusion detection system by Ali, Mohammed Hasan

“…However, the internal power parameters (weight and basis) of FLN are initialized at random, causing the algorithm to be unstable. …”
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Modified Seird model: a novel system dynamics approach in modelling the spread of Covid-19 in Malaysia during the pre-vaccination period by Zulkarnain, Norsyahidah, Mohammad, Nurul Farahain, Ahmed Shogar, Ibrahim Adam

“…This study implemented the preliminary stage of forecasting the COVID-19 data using the proposed SEIRD model and highlighted the importance of parameter optimization. …”
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IoT-based Machine Learning Comparative Models of Stream Water Parameters Forecasting for Freshwater Lobster by Bakhit, Abdelmoneim Ahmed, Nur Syahirah, Mohd Sabli, Mohd Faizal, Jamlos, Mohd Aminudin, Jamlos, N. H., Ramli, Muhammad Aqil, Hafizzan Nordin, Alhaj, Nura Abdalrhman, Ali, Ehtesham

“…Our findings underscore the efficacy of ARIMA for comprehensive water quality via stream prediction while highlighting the nuanced strengths and weaknesses of each model in forecasting specific parameters. This study contributes to the aquaculture literature by providing a nuanced comparative analysis of predictive models tailored to freshwater lobster farming, emphasizing the imperative role of stream predictive modelling. …”
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Improved model for blood glucose control using Multi-Parametric Model Predictive Control (MP-MPC) / Nur Farhana Mohd Yusof by Mohd Yusof, Nur Farhana

“…As a result, we managed to have a good correlation on interactions between the parameters in glucose-insulin intervention. For model validation purpose, actual patient data which refers to data of critically ill patients in this research are used due to scarcity of data available for type 1 diabetes patient in Malaysia. …”
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Classification of Cognitive Frailty in Elderly People from Blood Samples using Machine Learning by Idris, S., Badruddin, N.

“…This paper proposes a machine learning model to classify patients into different levels of CF, using parameters from blood samples. …”
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Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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Evaluating and predicting overall equipment effectiveness for deep water disposal pump using ANNGA analysis approach / Soud Al-Toubi, Babakalli Alkali, David Harrison and Sudhir C.... by Al Toubi, Soud, Harrison, David, C.V., Sudhir

“…ANN-GA analysis results indicated were very close and matched with the actual values. The model framework and analysis presented are used to develop a decision support tool for managers for early intervention to minimize system deterioration, reduce maintenance costs and increase productivity.…”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

“…The performance of SVM can be affected by hyperparameters, which are kernel scale and known as gamma and regularization parameters (C). A metaheuristic algorithm is introduced to optimise the hyperparameters. …”
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