Search Results - (( parameter optimization window algorithm ) OR ( variable active learning algorithm ))

An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks by Al-Kharasani, Ameen Mohammed Abdulkarem, Othman, Mohamed, Abdullah, Azizol, Kweh, Yeah Lun

“…This article analyses and evaluates a new time sliding window traffic marker algorithm called the Optimized time sliding window Three Colour Marker (OtswTCM). …”
Get full text
Get full text
Get full text

Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
Get full text
Get full text

Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm by Muthana, Shatha Abdulhadi, Ku Mahamud, Ku Ruhana

“…This research aims to find the optimal parameter values for the Pareto Ant Colony System (PACS) algorithm, which is used to obtain solutions for the generator maintenance scheduling problem. …”
Get full text
Get full text
Get full text

Design of intelligent Qira’at identification algorithm by Kamarudin, Noraziahtulhidayu

“…The process of the SPAP Algorithm is to extend parameters of the Affine Projection Block with two different selections of windowing length that affect the final accuracy on pattern classification. …”
Get full text
Get full text

Development of an education simulator for particle swarm optimization in solving economic dispatch problems: article / Mohd Hafiz Mat Hussain by Mat Hussain, Mohd Hafiz

“…In the developed simulator, users are able to set the parameters that have influences on particle swarm optimization performance. …”
Get full text
Get full text

Development of an education simulator for particle swarm optimization in solving economic dispatch problems / Mohd Hafiz Mat Hussain by Mat Hussain, Mohd Hafiz

“…In the developed simulator, users are able to set the parameters that have influences on particle swarm optimization performance. …”
Get full text
Get full text

Efficient management of Top-k queries over Uncertain Data Streams with dynamic Sliding Window Model by Raja Wahab, Raja Azhan Syah

“…This method reduces computational costs by efficiently handling the insertion and exit policy for the appropriate tuple candidates within a specified window frame. The experiments in this study compare the SWMTop-kDelta algorithm with two previous researchers and two baseline approach algorithms to evaluate their effectiveness. …”
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

Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
Get full text
Get full text

Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning by Yingbei, Niu, Chai, Soo See

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

Adaptive medium access control protocol of Wifi-Halow for home machine-to-machine network by Liew, Jiun Terng

“…Besides, the parameters of new mechanism are not defined optimally even though the procedure is detailed. …”
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

Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
Get full text
Get full text
Get full text

Predictive Analytics Of Cigs Solar Cell Using A Combinational Gra-Mlr-Ga Model by Salehuddin, Fauziyah, Kaharudin, Khairil Ezwan, Mohd Zain, Anis Suhaila, Roslan, Ameer Farhan

“…Thus, this paper proposes a newly predictive analytics using a combination of Grey relational analysis (GRA), multiple linear regressions (MLR) and genetic algorithm (GA) to optimize the CIGS solar cell parameters for better device performances. …”
Get full text
Get full text
Get full text

Orthogonal Frequency Division Multiple Access resource unit allocation algorithms for IEEE 802.11AX medium access control protocol by Zazali, Azyyati Adiah

“…First is the Versatile Shuffle Recomputation Resource Units (VSR-RUs), which use the Fisher-Yates shuffling algorithm to optimize RU utilization and reduce collisions. …”
Get full text
Get full text
Get full text

Mathematical model of energy saving glass coating shape design using binary harmony search for better signal transmission by Jasmi, Muhammad Izzuddin

“…A well-designed algorithm is able to generate an optimized irregular shape design that can result in less attenuation on the transmission signal. …”
Get full text
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

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