Search Results - (( data normalization path algorithm ) OR ( variable active learning algorithm ))

Dynamics and control of underactuated systems with applications in robotics / Ahmad Azlan Mat Isa … [et al.] by Mat Isa, Ahmad Azlan

“…An ANN modal was trained using the experimentally obtained data and then used to predict the path of the passive joint that is positioned by the dynamic coupling of the active joint. …”
Get full text
Get full text

Wide area measurement system in the IEEE-14 bus system using multiobjective shortest path algorithm for fault analysis by Awalin, Lilik J., Syahirah, Abd Halim, Jafferi, Jamaludin, Nor Azuana, Ramli

“…The distances of the normal path (without simulated fault) and the new path (with simulated fault) were recorded. …”
Get full text
Get full text
Get full text

Restaurant locator using Djikstra Algorithm / Mohamad Aliff Hakimi Lukman Hakim by Lukman Hakim, Mohamad Aliff Hakimi

Get full text
Get full text

Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP). by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

“…Their ability as a colony to find paths or routes to the food sources has inspired the development of an algorithm namely Ant Colony System (ACS). …”
Get full text
Get full text

Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

Intelligent motion planning of a mobile robot by using convolutional neural network / Siti Asmah Abdullah by Siti Asmah, Abdullah

“…By the path reference created by A* algorithm the robot is capable in optimizing its path to reach the designated destination. …”
Get full text
Get full text
Get full text

Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
Get full text
Get full text

A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm by Masood, Kamal

“…Interpolation scheme based on the multiaixality of stresses is suggested for the determination of coefficients of the model for different loading paths. Material parameter including stress sensitivity factor for normal or shear stress can be incorporated to improve the calibration process. …”
Get full text
Get full text

Improving Channel Assignment for Vehicular Ad-hoc Sensor Network in Disaster Management System by Chiu Shoon, Sia

“…Moreover, an average of 22.91% for LTE-AIC with respect to normal LTE-A and 38.63% compared to LTE for high data rate. …”
Get full text
Get full text
Get full text

A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
Get full text

Deadline guarantee for scientific workflow using dynamic scheduling algorithms on IaaS clouds by Alqaisy, Sarah Abdulrahman Shukur

“…We will conduct a simulation experiment of scientific workflow algorithms with both of the algorithms mentioned above. …”
Get full text
Get full text

Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
Get full text
Get full text
Get full text

Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
Get full text
Get full text
Get full text

Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
Get full text
Get full text

Classification of Students' Performance in Computer Programming Course According to Learning Style by Norwawi, NM, Abdusalam, SF, Hibadullah, CF, Shuaibu, BM

“…The findings show that that student's good performance in programming courses has a visual, active and sequential learning style.…”

Classifying corporates default and non-default using machine learning Artificial Neural Network: multilayer perceptron / Nur Insyirah Mohamad Radzi, Murni Salina Rosidi and Nur Asy... by Mohamad Radzi, Nur Insyirah, Rosidi, Murni Salina, Zailand, Nur Asyura Izzati

“…Asset volatility is found to be the most significant independent variable. Therefore, ANN is a machine learning algorithm that uses multiple layers perceptron to solve complex problems and predict analytics.…”
Get full text
Get full text

A smart marker-based indoor navigation system by Teoh, Zhen Quan

“…The proposed system also employs algorithms to calculate the shortest path for navigation and estimate the user position for localization when the user scans a marker. …”
Get full text
Get full text

An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

“…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
Get full text
Get full text

Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
Get full text
Get full text