Search Results - (( developing negative tree algorithm ) OR ( java implication based algorithm ))*

Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

“…This work proposes a new spatial decision tree algorithm namely the extended spatial ID3 decision tree algorithm to classify hotspots occurrence from a forest fires dataset that contains point, line and polygon features. …”
Get full text
Get full text

Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

“…In this research, Support Vector Machine (SVM) machine learning detection & prevention algorithm were developed to detect this type of attacks Two other techniques were benchmarked decision tree and Naïve Bayes. …”
Get full text
Get full text
Get full text
Get full text

Classification model for hotspot occurrences using a decision tree method by Sitanggang, Imas Sukaesih, Ismail, Mohd Hasmadi

“…This work demonstrates the application of a decision tree algorithm, namely the C4.5 algorithm, to develop a classification model from forest fire data in the Rokan Hilir district, Indonesia. …”
Get full text
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

Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

“…For the objective of classifying FI in terms of fraud or not, the Intelligent Information System for Financial Institutions (IISFI) relying on Supervised ML (SML) Algorithms has been created in this work. Bayesian Belief Network, Neural Network, Decision trees, Naïve Bayes, and Nearest Neighbor has been compared for the purpose of classifying FI risks using the performance measures asfalse positive rate, true positive rate, true negative rate, false negative rate, accuracy, F-Measure, Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Square Error (RMSE), Med AE, Receiver Operating Characteristic (ROC) area,Precision Recall Characteristic (PRC) area, and measures of PC. …”
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

Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones by Khudhayer, Wael A.

“…The shading efficiency represented the percentage of the shaded area to the total floor area of the pedestrian zone, while the targeted shading efficiency indicated the preferable shading requirements for the pedestrian. The development of the prediction tool was conducted base on integrating three sequenced algorithms, which are sun position algorithm, shadow length and position algorithm, and expansion limit algorithm. …”
Get full text
Get full text

Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
Get full text
Get full text

Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat by Selamat, Nur Syuhada

“…As with most studies,careful attention was paid to false positive and false negative rates which reduce their overall detection accuracy and effectiveness.The result showed that the Random Forest algorithm is the best detection accuracy compares to others classifier with 99 % on a relatively small dataset. …”
Get full text
Get full text

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

Computationally-efficient path planning algorithms in obstacle-rich environments based on visibility graph method by Abdul Latip, Nor Badariyah

“…Cun·ent studies have been focused on developing path planning algorithms to satisfy the criteria of path planning namely minimum path length, low computation time and complete, i.e., it gives positive result if a path is available or negative if otherwise. …”
Get full text
Get full text
Get full text
Get full text

Development of high speed booth multiplier with optimized stuck-at fault implementation by Mohammed Khalid, Muhammad Nazir, Wan Hasan, Wan Zuha, Sulaiman, Nasri, Wagiran, Rahman

Get full text
Get full text

Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate by Nadimalla, Altamashuddinkhan, Masjuki, Siti Aliyyah, Gubbi, Abdullah, Khan, Anjum, Mokashi, Imran

“…Machine Learning (ML) and Artificial Intelligence (AI) are closely intertwined and represent the latest cutting-edge technologies that facilitate the development of intelligent prototypes. Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
Get full text
Get full text
Get full text
Get full text

Sentiment analysis of customer reviews for Konda Kondi Cafe & Bistro by Abd Azizul Rahman, Munirah Syafiqah

“…The data was pre-processed using tokenization, stop-word removal, and stemming techniques to ensure quality inputs. Machine learning algorithms such as Support Vector Machine (SVM), Naive Bayes (NB), and Decision Tree (DT) were applied using RapidMiner to build classification models. …”
Get full text
Get full text

Green building factor in machine learning based condominium price prediction by Masrom, S., Mohd, T., Rahman, A.S.A.

“…The negative impact of massive urban development promotes the inclusion of green building aspects in the real estate and property industries. …”
Get full text
Get full text

A new integrated approach for evaluating sustainable development in the electric vehicle sector by Lu, Wen Min, Chou, Chienheng, Ting, Irene Wei Kiong, Liu, Shangming

“…Third, this study uses the classification & regression tree (CART), random forest, and eXtreme gradient boosting (XGBoost) algorithms to assist managers in identifying the key predictive variables for further classification and prediction. …”
Get full text
Get full text
Get full text
Get full text

Comparative Analysis of Gene Expressed in Trunking and Non-Trunking Metroxylon sagu Leaves Utilizing Transcriptome Sequencing by Wei Jie, Yan

“…Under normal conditions, the sago palm develops its trunk after 4 - 5 years of being planted. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

“…A PLS regression is used on NIR spectra to implement the prediction of ergosterol concentration which shows good corelation of R = 0.861 between the ergosterol concentration and oil palm NIR spectra. Four different ML algorithms are tested for prediction of G. boninense infection: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested which depicted DT algorithm achieves a satisfactory overall performance with high accuracy up to 93.1% and F1-score of 92.6% compared to other algorithms. …”
Get full text
Get full text
Get full text

Development of Malaysia breast cancer survival prognostic tool (myBeST) for prediction of survival probability among women with breast cancer in Malaysia by Kadir, Mohd Nasrullah Nik Ab.

“…Objective: The study aimed to develop predictive models for survival among women with breast cancer in Malaysia, to compare its performance with PREDICT and the model’s algorithm was incorporated to develop a web-based Malaysian Breast Cancer Survival Prognostic Tool (myBeST). …”
Get full text
Get full text