Spider monkey optimizations: application review and results by Abualigah, Laith

“…Optimization algorithms are applied to find efficient solutions in different problems in several fields such as the routing in wireless networks, cloud computing, big data, image processing and scheduling, and so forth. …”
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Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions by Liu, Wenpeng

“…This paper reviews testing procedures, data analysis, updated algorithms used for joint detection, and discusses the latest round of testing in samples with simulated joints at various angles along the borehole.…”
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

“…</p><h3>Methods</h3><p dir="ltr">Using historical data (2008-2020), an accurate prediction model using machine learning methods was developed and incorporated into a mobile app. …”

A collaborative filtering recommendation framework utilizing social networks by Aamir Fareed (17019087)

Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem by Assaker, Guy

“…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. …”
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Towards Scalable Process Mining Pipelines by Mohamed, Belal

“…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …”
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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System by Abu Zitar, Raed

“…We research and test the design of the right neural networks that achieves our goal. A modern algorithm was improvised for this reason. For our proposed recommendation system, a database program was created to store data and include details in the analysis of course learning outcomes. …”
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Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain by Jun Zhu (84054)

“…The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. …”

Enhanced simulated evolution algorithm for digital circuit design yielding faster execution in a larger solution space by Sait, Sadiq M.

“…Evolutionary algorithms have been studied by several researchers for the design of digital circuits. …”
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A Prioritized Uplink Call Admission Control Algorithm for 3G WCDMA Cellular Systems with Multi-Services by Al-Qahtani, Salman

“…The algorithm uses the effective load as an admission criterion and applies different thresholds for new and handoff calls. …”
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Exploring the Impact of Explainable Artificial Intelligence on Decision-making in Healthcare by MOHAMMAD, AHMAD HASAN

“…The study analyses the benefits and limitations of applying XAI in healthcare decision-making processes through an exhaustive analysis of current literature and empirical data. It investigates how XAI might increase AI algorithm transparency, allowing healthcare practitioners to better comprehend the reasoning behind AI-generated suggestions or forecasts. …”
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AI-based remaining useful life prediction and modelling of seawater desalination membranes by Al Ali, Fajer

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Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter by Mena S. ElMenshawy (17983807)

“…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …”

Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

“…The paper proposes a concurrent job scheduling algorithm in a multi-energy data source environment using Apache Spark. …”

Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures by Leduc, Guillaume

“…To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. We validate our closed-form solution for the option pricing through simulations employing the generalized antithetic variates Monte-Carlo technique. …”
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Implementation and Comparison of Particle Swarm Optimization and Genetic Algorithm Techniques in Combined Economic Emission Dispatch of an Independent Power Plant by Shahbaz Hussain (9765320)

“…The results are of great significance as the real data of an IPP is used and imply that the performance of PSO is better than that of GA in case of CEED for finding the optimal solution concerning fuel cost, emission, convergence characteristics, and computational time. …”

Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

“…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”

Software defect prediction. (c2019) by Moussa, Rebecca

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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

“…<p dir="ltr">In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the complexity of query analysis. …”

Bird’s Eye View feature selection for high-dimensional data by 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. …”