Search Results - (( developing dynamic bayes algorithm ) OR ( java implication based algorithm ))

Android Mobile Malware Classification Based on System Call and Permission Using Tokenization by Intan Nurfarahin Binti Ahmad

Android Ransomware Detection Based on Dynamic Obtained Features by Abdullah Z., Muhadi F.W., Hamid I.R.A., Foozy C.F.M., Madihah Mohd Saudi

Sales prediction of religious product and services of Mutawwif Haramain Travel & Tours using predictive analytics by Mohd Sabri, Nurul Ainin Qistina

“…Sales prediction in the religious services sector is challenging due to seasonal, cultural, and economic factors, which make traditional methods less reliable. This research develops a predictive model for sales prediction at Mutawwif Haramain Travel & Tours, utilizing machine learning algorithms, specifically Decision Tree, Random Forest, and Naive Bayes, to uncover patterns in customer behavior and seasonal demand. …”
Get full text
Get full text

Classification of polymorphic virus based on integrated features by A Hamid, Isredza Rahmi, Subramaniam, Sharmila, Sutoyo, Edi, Abdullah, Zubaile

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

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

iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems by Azad, Saiful, Mahmud, Mufti, Kamal Zuhairi, Zamli, Kaiser, M. Shamim, Jahan, Sobhana, Razzaque, Md Abdur

“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
Get full text
Get full text
Get full text

Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

“…More significantly, this paper empirically discusses and compares the performances of six supervised machine learning algorithms, known as K-Nearest Neighbors (K-NN), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), Naïve Bayes (NB), and Logistic Regression (LR), which are commonly used in the literature for detecting malware apps.…”
Get full text
Get full text
Get full text
Get full text

Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak by Rajogoval, Illayakantthan

“…The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
Get full text
Get full text