Search Results - (( pattern decision modelling algorithm ) OR ( java application optimization algorithm ))

Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

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Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System by Zulkifli, Abdul Hayy

“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Reservoir water release dynamic decision model based on spatial temporal pattern by Suriyati, Abdul Mokhtar

“…Thus, this study proposed dynamic reservoir water release decision model that utilize both spatial and temporal information in the input pattern. …”
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A spatial decision support system framework for optimization of cropping pattern and water resources allocation at pasargard plains, fars province, Iran by Ghasemi, Mohammad Mehdi

“…A unit response matrix groundwater model was coupled with a modified version of Genetic Algorithm (GA) in order to optimize cropping patterns and water allocation decisions. …”
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Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

“…Focused on computational intelligence models, this thesis describes in-depth investigations on two possible directions to design robust and flexible pattern classification models with high performance. …”
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An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability by Bouke, Mohamed Aly, Abdullah, Azizol

“…We preprocess the data to create versions with and without pattern leakage and train and test six ML models: Decision Tree (DT), Gradient Boosting (GB), K-neighbours (KNN), Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR). …”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

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A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application by Mostafa S.A., Mustapha A., Mohammed M.A., Ahmad M.S., Mahmoud M.A.

“…Accident prevention; Assisted living; Computer circuits; Fuzzy logic; Multi agent systems; Adjustable autonomy; Ambient assisted living; Autonomous decision; Complex environments; Elderly remote care; Fall detection; Fuzzy logic control; Movement monitoring; Autonomous agents; aged; Article; automation; decision making; falling; fuzzy logic; human; movement (physiology); patient autonomy; patient monitoring; priority journal; algorithm; automated pattern recognition; computer simulation; movement (physiology); physiologic monitoring; procedures; theoretical model; Aged; Algorithms; Computer Simulation; Fuzzy Logic; Humans; Models, Theoretical; Monitoring, Physiologic; Movement; Pattern Recognition, Automated…”

Data mining techniques for disease risk prediction model: A systematic literature review by Ahmad W.M.T.W., Ghani N.L.A., Drus S.M.

Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

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A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection by Jia, Lu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

“…Besides, the interpretable model can help us demonstrate the complex and overlapped pattern of intrusions and analyze the pattern of various intrusions.…”
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Machine learning predictions of stock market pattern using Econophysics approach by Roslan, Nur Nadia Hani, Abdullah, Shahino Mah

“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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Feature selection with integrated Gaussian seahorse optimization data mining for cross-border business cooperation between the Malaysian medical industry and tourism industry by Ma, Yuaner, Jabar, Juhaini, Abdul Aziz, Nor Azah

“…The integrated GSH-DM model then applies the Gaussian Seahorse Optimization algorithm to optimize the data mining process, enhancing the accuracy and efficiency of pattern discovery. the GSH-DM model, this study aims to uncover hidden patterns, relationships, and predictive models that can guide decision-making and strategy development for cross-border business cooperation. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms by Anuar N.K., Bakar A.A., Ahmad A.R., Yussof S., Rahim F.A., Ramli R., Ismail R.

Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…The pandemic has resulted in unpredictable customers’ purchasing patterns post-pandemic has rendered heuristic-based forecasting large forecast errors, which leads to poor decision-making. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…With 89.39 test accuracy and 99.82 train accuracy, the Random Forest model performs well. The Decision Tree model has 89.19 test and 99.94 train accuracy. …”
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