Search Results - (( java implication based algorithm ) OR ( parameter _ prevention algorithm ))

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

“…This criterion is responsible for adding only the important terms to each rule, thus discarding noisy data. The ACS algorithm is designed to optimize the IR parameter during the learning process of the Ant-Miner algorithm. …”
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Quality of service management algorithms in WiMAX networks by Saidu, Ibrahim

“…Moreover, an improved sleep mode control algorithm has been introduced to reduce the high energy consumption of the standard sleep mode algorithm. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

“…Under the background of big data, it is of practical significance to prevent loan risk by the machine learning algorithm. …”
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Automatic control of flotation process using computer vision by Saravani, Ali Jahed

“…Bubble size distribution which is regarded as the most important characteristics of froth structure, is being addressed in this thesis by using a segmentation algorithm. A marker based watershed algorithm had been adopted and improved so as to prevent the over segmentation of big bubbles and able to adapt itself with different scenario of froth images. …”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.

“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”

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

DRIVER FATIGUE ACCIDENT PREVENTION USING EYE BLINK SENSOR by AZIZAN, SITI ROSMA

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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…Thus, this study proposes the development of algorithms to detect and classify jamming attacks using a set of parameters on the physical layer and MAC in MANET. …”
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A Multidimensional Search Space Using Interactive Genetic Algorithm by Farooq, H., Zakaria, M.N., Hassan, M.F., Sulaiman, Suziah

“…For experiment, we have selected Parametric L-System, in which both symbols and numerical parameters are evolved using Genetic Algorithm (GA). …”
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Autonomous flight algorithm of a quadcopter sensing system for methane gas concentration measurements at landfill site by Bashi, Omar Ibrahim Dallal

“…During the experimentation, accurate methane gas concentration measurements at landfill sites were obtained using the algorithm for autonomous flight, with the implementation of optimal quadcopter flight parameters and gas sensor mounting arrangements. …”
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Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems by Mok, Ren Hao, Mohd Ashraf, Ahmad

“…NLSFA constrains gradient approximation within boundaries, preventing excessively large approximations that lead to divergence but at the cost of an additional optimization parameter. …”
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Location accuracy improvement in bluetooth low energy based indoor positioning system for remote asset monitoring / Dasmond Roy Philips by Dasmond Roy , Philips

“…This research project mainly aims to improve location accuracy of the asset tracking system through implementation of machine learning algorithms and parameters tuning. Machine learning algorithms that were involved in this research are Support Vector Regression (SVR), Decision Tree (DT) and K-Nearest Neighbor (KNN). …”
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Development of auto-tracking mobile robot by Ahmad Shahrizan, Abdul Ghani, Suresh, Sundarajoo

“…Besides that, this algorithm also prevents tracking loss due to object color appears in the background.…”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

“…Condition monitoring is a major component in predictive maintenance which monitors the condition and identifies significant changes of the machinery parameter to perform early detection and prevent equipment defects that could cause unplanned downtime or incur unnecessary expenditures. …”
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Optimisation and control of semi-active suspension using genetic algorithm for off-road full vehicle by BenLahcene, Zohir, Faris, Waleed Fekry, Ihsan, Sany Izan, Ridhuan Siradj , Fadly Jashi Darsivan

“…In solving this problem, the genetic algorithms have consistently found near-optimal solutions within specified parameters ranges for several independent runs.…”
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Efficient dynamic DNA-based block cipher algorithm by Chng, Chern Wei

“…The significance of block cipher algorithms lies in their versatility and resilience. …”
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Characterisation of pineapple cultivars under different storage conditions using infrared thermal imaging coupled with machine learning algorithms by Mohd Ali, Maimunah, Hashim, Norhashila, Abd Aziz, Samsuzana, Lasekan, Ola

“…Principal component analysis was applied for feature reduction in order to prevent any effect of significant difference between the selected features. …”
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Improvement of Auto-Tracking Mobile Robot based on HSI Color Model by Sundarajoo, Suresh, Ahmad Shahrizan, Abdul Ghani

“…Besides that, this algorithm also prevents tracking loss due to object color appears in the background.…”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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