Estimating Construction Project Duration Using a Machine Learning Algorithm حسب Nasr, Joshua

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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering حسب Abu Zitar, Raed

الموضوعات:

A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System حسب Ameema Zainab (16864263)

الموضوعات:

Web Based Online Hybrid Teaching Method of Network Music Course حسب Abu Zitar, Raed

"…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …"
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing حسب Al Sadawi, Alia

"…A Master of Science thesis in Engineering Systems Management by Alia Al Sadawi entitled, "Efficient Dynamic Cost Scheduling Algorithm for Data Batch Process," submitted in May 2016. …"
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Bird’s Eye View feature selection for high-dimensional data حسب Samir Brahim Belhaouari (16855434)

"…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …"

Using machine learning algorithm for detection of cyber-attacks in cyber physical systems حسب Almajed, Rasha

"…We present the new framework for the detection of cyberattacks, which makes use of AI and ML. We begin a process to cleaning up the data in the CPS database by applying normalization to eliminate errors and duplication. …"
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Learning-Based Space-Time Adaptive Processing حسب El Khatib, Alaa

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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain حسب Al Sadawi, Alia

"…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …"
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images حسب Sajun, Ali Reza

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Genetic and heuristic algorithms for regrouping service sites. (c2000) حسب Tabbara, Hiba

الموضوعات: "…Genetic algorithms -- Data processing…"
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Design of acoustic absorbing metasurfaces using a data-driven approach حسب Hamza Baali (14603380)

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Three-phase approach for curriculum-based course timetabling problem. (c2012) حسب Jazzar, Hanaa Salem El-

الموضوعات: "…Scheduling -- Data processing…"
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Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) حسب Kawash, Jalal Y.

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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition حسب Dabeeruddin Syed (16864260)

"…Whilst different models are proposed for STLF, they are based on small historical datasets and are not scalable to process large amounts of big data as energy consumption data grow exponentially in large electric distribution networks. …"

A genetic algorithm for corrective retesting. (c1995) حسب Fakih, Khaled A.

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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection حسب Zina Chkirbene (16869987)

"…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …"

DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data حسب Assaf, Ali

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A Survey of Data Clustering Techniques حسب Sobeh, Salma

الموضوعات: "…Cluster analysis -- Data processing…"
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Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) حسب Tay, Bilal M.

"…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …"
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