Search Results - (( developing future tree algorithm ) OR ( java application reoptimize algorithm ))

Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

“…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
Get full text
Get full text

A study of graduate on time (GOT) for Ph.D students using decision tree model by Chin, Wan Yung, Ch’ng, Chee Keong, Mohd Jamil, Jastini

“…Therefore, this study aims to classify the Ph.D students into the group of “GOT achiever” and “non-GOT achiever” by using decision tree models. Historical data that related to all Ph.D students in a public university in Malaysia has been obtained directly from the database of Graduate Academic Information System (GAIS) in order to develop and compare the performance of decision tree models (Chi-square algorithm, Gini index algorithm, Entropy algorithm and an interactive decision tree). …”
Get full text
Get full text
Get full text

Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

Development of trees management system using radial basis function neural network for rain forecast by Auzani, Hasnul, Hashim, Khairusy Syakirin Has-Yun, Mohd Nazri, Farah Aniza

Get full text
Get full text
Get full text

Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman by Abdul Aziz, Maslina, Mustakim, Nurul Ain, Abdul Rahman, Shuzlina

“…The result indicated that the highest accuracy of 89.34% was achieved by the Random Tree algorithm, while the rule-based algorithm PART reached an accuracy of 87.56%. …”
Get full text
Get full text

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

Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.] by Mohd Fuzi, Mohd Faris, Mohd Shahirudin, Syamir, Abd Halim, Iman Hazwam, Jamaluddin, Muhammad Nabil Fikri

“…The results indicated that the Decision Tree and Random Forest algorithms provided the best detection accuracy at 96%, followed by the K-NN algorithm at 95%. …”
Get full text
Get full text
Get full text

Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

Forecasting Malaysian gold price using random forest / Muhammad Nur Firmanrulah Samsudin by Samsudin, Muhammad Nur Firmanrulah

Get full text
Get full text

Developing an app for streamlined inventory tracking with barcode scanning and load planning optimization by Teng, Yan Xin

“…Keywords: Inventory Management, Barcode Scanning, Load Planning, Binary Tree Bin Packing Algorithm, Mobile Application Development. …”
Get full text
Get full text

White root disease auto-detection system for rubber trees based on dynamic electro-biochemical latex properties / Mohd Suhaimi Sulaiman by Sulaiman, Mohd Suhaimi

“…From there, this would consequently help to increase the yield of natural rubber latex in the future by preventing the disease from spreading to other trees.…”
Get full text
Get full text

A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

Get full text
Get full text
Get full text
Get full text

Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

Get full text
Get full text
Get full text

An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery by Aisyah Marliza Muhmad Kamarulzaman, Wan Shafrina Wan Mohd Jaafar, Siti Nor Maizah Saad, Hamdan Omar, Mohd. Rizaludin Mahmud

“…This research implemented a technique for detecting, segmenting, classifying, and measuring tree stumps by using the Multiresolution Segmentation Algorithm method. …”
Get full text
Get full text
Get full text

Quantum Processing Framework And Hybrid Algorithms For Routing Problems by Soltan Aghaei, Mohammad Reza

“…Next, the framework of QAPU was designed and developed. For this purpose, some gates and connections were projected in the framework which could be applied for future quantum algorithms. …”
Get full text
Get full text

Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
Get full text
Get full text
Get full text
Get full text

Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

“…Additionally, pre-processing is conducted using the RapidMiner application prior to mapping the cleaned data with three distinct algorithms for predictive analysis: Decision Tree, Random Forest, and Multiple Linear Regression techniques. …”
Get full text
Get full text

Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia by Latif S.D., Hazrin N.A.B., Younes M.K., Ahmed A.N., Elshafie A.

“…It is crucial for developing countries such as Malaysia to be able to accurately predict future municipal solid waste generations in order to achieve high-quality waste management. …”

Classification prediction of PM10 concentration using a tree-based machine learning approach by Wan Nur Shaziayani, Ul-Saufie, Ahmad Zia, Mutalib, Sofianita, Mohamad Noor, Norazian, Zainordin, Nazatul Syadia

“…Machine learning approaches have the potential to predict and classify future PM10 concentrations accurately. Therefore, in this study, three machine learning algorithms—namely, decision tree (DT), boosted regression tree (BRT), and random forest (RF)—were applied for the prediction of PM10 in Kota Bharu, Kelantan. …”
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

“…Our result provides a framework for future studies on the use of predictive models in the development of an early warning system.…”
Get full text
Get full text
Get full text
Get full text