Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”

Revolutionizing sustainable supply chain management: A review of metaheuristics by Abualigah, Laith

“…The paper also identifies the key factors that influence the success of using metaheuristics for SSCM, such as the choice of algorithm, problem complexity, and data quality. …”
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …”
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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. …”

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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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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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. …”

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. …”

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. …”

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. …”

Current trends and future orientation in diagnosing lung pathologies: A systematic survey by Noorizadeh, Mohammad

“…These VOCs can aid in the diagnosis of lung pathologies such as pneumonia. The CV processing method involves the application of advanced imaging techniques and machine learning algorithms to scrutinize and diagnose lung pathologies and ventilator-associated pneumonia (VAP). …”
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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. …”

Software defect prediction. (c2019) by Moussa, Rebecca

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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. …”

Autonomous 3D Deployment of Aerial Base Stations in Wireless Networks with User Mobility by Islambouli, Rania

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Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles by Wadi, Ali

“…The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …”
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Performance Prediction Using Classification by MOOLIYIL, GITA

“…The use of classification as a data mining approach for performance prediction has been studied by many eminent researchers. …”
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