Search Results - (( parallel optimization path algorithm ) OR ( variable reduction learning algorithm ))

Tool path generation of contour parallel based on ant colony optimisation by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

“…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
Get full text
Get full text

Minimizing machining airtime motion with an ant colony algorithm by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

Get full text
Get full text

OPTIMAL DATAPATH DESIGN FOR A CRYPTOGRAPHIC PROCESSOR: THE BLOWFISH ALGORITHM by Zain Ali, Noohul Basheer, Noras, James

Get full text
Get full text

Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
Get full text
Get full text
Get full text

A novel large-bit-size architecture and microarchitecture for the implementation of Superscalar Pipeline VLIW microprocessors by Lee, Weng Fook

“…Different adder architectures are investigated for suitability on synthesis implementation of large data bus size adder for efficient usage within the ALU. An adder algorithm using repetitive constructs in a parallel algorithm that allows for efficient and optimal synthesis for large data bus size is proposed as a suitable implementation for the adder within the ALU. …”
Get full text

Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…The experimental results showed that the accuracy of the algorithm over the NSL-KDD dataset was 99.72%, with a memory reduction of 10%. …”
Get full text
Get full text

Variable step size least mean square optimization for motion artifact reduction: A review by Zailan, K.A.M., Hasan, M.H., Witjaksono, G.

“…Therefore, we propose a research to formulate an improved motion artifact reduction approach using variable step-size least mean square (VSSLMS). …”
Get full text
Get full text

Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

“…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
Get full text
Get full text

A hybridisation of adaptive variable neighbourhood search and large neighbourhood search: Application to the vehicle routing problem by Sze, Jeeu Fong, Salhi, S., Wassan, N.

“…In this paper, an adaptive variable neighbourhood search (AVNS) algorithm that incorporates large neighbourhood search (LNS) as a diversification strategy is proposed and applied to the capacitated vehicle routing problem. …”
Get full text
Get full text
Get full text

A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks by Chien, Stephen Lim Een, Raja Maamor Shah, Raja Noor Farah Azura, Othman, Mohamed

“…A tree visualisation was constructed based on its connectivity to enable the generation of formulae for optimal diameter and average optimal path lengths. …”
Get full text
Get full text

Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques by Mustafa, Ahmed Sudad

“…In this thesis, a hybrid detection algorithm mechanism has been proposed which combines two detection algorithms based on nodes’ trustworthiness and energy consumption in a parallel manner in order to detect the black hole nodes. …”
Get full text
Get full text
Get full text

Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Derisf, Mustafa, Aqil Burney, S.M.

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
Get full text
Get full text
Get full text

Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, Burney, S.M.Aqil

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
Get full text
Get full text
Get full text

Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, Aqil Burney, S.M.

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
Get full text
Get full text
Get full text

Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Riswan Efendi, Riswan Efendi, Mohd. Nawi, Nazri, Mat Deris, Mustafa, Aqil Burney, S.M.

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
Get full text
Get full text
Get full text

Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning by Ahmed Abo Mosali, Najm Addin Mohammed

“…In this thesis, the Twin Delayed Deep Deterministic Policy Gradient Algorithm (TD3), as one recent and composite architecture of reinforcement learning (RL), has been explored as a tracking agent for the problem of UAV-based target tracking. …”
Get full text
Get full text
Get full text
Get full text

Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Riswan Efendi, Riswan Efendi, Nazri Mohd. Nawi, Nazri Mohd. Nawi, Mustafa Mat Deris, Mustafa Mat Deris, S.M.Aqil Burney, S.M.Aqil Burney

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
Get full text
Get full text
Get full text

Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
Get full text
Get full text
Get full text

Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
Get full text
Get full text
Get full text

Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efend, Riswan, Mohd. Nawi, Nazri, Mat Derisf, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
Get full text
Get full text
Get full text