Search Results - (( developing a predictor algorithm ) OR ( java implication based algorithm ))

Formulation of macro-micro safety predictors in high-rise construction sites based on dematel algorithm by Kang, Chun Xiang

Get full text
Get full text

Development of artificial neural network models for predicting lipid profile using smartMF electrical parameters / Ahmad Zulkhairi Zulkefli by Ahmad Zulkhairi , Zulkefli

“…For TG, the LM algorithm with a testing accuracy of 76.7%, sensitivity of 28.6% and specificity of 91.3% was selected. …”
Get full text
Get full text
Get full text

Predictor-corrector scheme in modified block method for solving delay differential equations with constant lag by Nurul Huda Abdul Aziz, Zanariah Abdul Majid, Fudziah Ismail

“…In this developed algorithm, each coefficient in the predictor and corrector formula are recalculated when the step size changing. …”
Get full text
Get full text
Get full text

Predictor-corrector scheme in modified block method for solving delay differential equations with constant lag by Abdul Aziz, Nurul Huda, Abdul Majid, Zanariah, Ismail, Fudziah

“…In this developed algorithm, each coefficient in the predictor and corrector formula are recalculated when the step size changing. …”
Get full text
Get full text
Get full text

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

Get full text
Get full text
Get full text

An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif by Sa’dan, Siti ‘Aisyah, Jantan, Hamidah, Abdul Latif, Mohd Hanapi

Get full text
Get full text

REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION by P ISKANDAR, YULITA HANUM

“…In order to overcome latency problem, this research is an attempt to suggest a new prediction algorithm based on heuristic that could be used to develop a more effective and general system for virtual training applications. …”
Get full text
Get full text

Neural network diagnostic system for dengue patients risk classification by Faisal, T., Taib, M.N., Ibrahim, Fatimah

“…By employing those predictors, 75 prediction accuracy has been achieved for classifying the risk in dengue patients using Scaled Conjugate Gradient algorithm while 70.7 prediction accuracy were achieved by using Levenberg-Marquardt algorithm. …”
Get full text
Get full text
Get full text

Diagonally multistep block method for solving Volterra integro-differential equation with delay by Baharum, Nur Auni, Abdul Majid, Zanariah, Senu, Norazak, Rosali, Haliza

“…It approximates two numerical solutions simultaneously within a block. The algorithm for the approximation solution is developed and the Newton-Cotes formulae are adapted in the DMB method to estimate the solution for an integral component. …”
Get full text
Get full text

Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: a cross-sectional SHAP-based analysis of NHANES 2009-2023 by Tang, Yan, Jia, Lei, Zhou, Junjun, Dou, Jin, Qian, Jingjuan, Yi, Xin, Soh, Kim Lam

“…The best-performing model was interpreted through SHapley Additive exPlanations analysis to identify the most influential predictors. A streamlined version incorporating the top 10 predictors was further developed and implemented as a user-friendly web-based risk estimation tool. …”
Get full text
Get full text
Get full text

Embedded System of DNA Exon Predictor using Hidden Markov Model by Habibi Husain, Arifin, Ahmad Nasir, Che Rosli, R. Badishah, Ahmad, Assoc. Prof. Dr., Suhartati, Agoos, Dr. Ir, Ferrianto, Gazali, M. Sc., Ir., Endang Djuana, ST. M. Eng., Md. Mostadjur, Rahman, Safarin, Samsudin

Get full text

Daily rainfall prediction using clonal selection algorithm by Noor Rodi, Nur Syazwani, Ismail , Amelia Ritahani, Abdul Malik, Marlinda

“…From the experiment, the results obtained more than 90% accuracy by using 100, 500 and 1000 numbers of detector which is promising that CSA can be a good predictor algorithm.…”
Get full text
Get full text
Get full text

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

“…Principle component analysis was used to determine which predictors were most reliable. Hybrid model development included the optimization of ANN coefficients (its weights and biases) using adaptive guided differential evolution algorithm. …”

Application of Krylov Subspace methods for solving Continuous Power Flow problem in voltage stability analysis of power system by Jasni, Jasronita

“…These developed algorithms are tested on 14, 118 and 300 IEEE bus systems. …”
Get full text
Get full text

Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data by Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair

“…Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. …”
Get full text
Get full text
Get full text
Get full text

Three-point Block Algorithm For Approximating Duffing Type Differential Equations by Ahmad Fadly Nurullah Rasedee, Mohammad Hasan Abdul Sathar, Najwa Najib, Nurhidaya Mohamad Jan, Siti Nor Aini Mohd Aslam, Siti Munirah Mohd

Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…The multilevel analysis based on logistic regression identified gender, socio-economic status (SES), household size and intervention measures as predictors while Monte Carlo study of local malaria predictors’ results was comparable to logistics especially when n is large (150,000) and with a lower precision level (0.000001). …”
Get full text
Get full text

Modeling of CO emissions from traffic vehicles using artificial neural networks by Al-Gbur, Omer Saud Azeez, Pradhan, Biswajeet, Mohd Shafri, Helmi Zulhaidi, Shukla, Nagesh, Lee, Chang Wook, Rizeei, Hossein Mojaddadi

“…The model was developed using six traffic CO predictors: number of vehicles, number of heavy vehicles, number of motorbikes, temperature, wind speed and a digital surface model. …”
Get full text
Get full text
Get full text

Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables by Che Dom, Nazri, Mohd Hardy Abdullah, Nur Athen, Dapari, Rahmat, Salleh, Siti Aekbal

“…Predictor variables included single, dual, and triple combinations of microclimatic inputs, and models were trained and validated using 10-fold cross-validation and a 70:30 train-test data split. …”
Get full text
Get full text
Get full text