Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment by Farhat Mahmood (15468854)

“…A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …”

Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care by Regina Padmanabhan (14231606)

“…Other highlights are (1) a novel set of easily available features for the prediction of the aforementioned clinical complications and (2) the use of data augmentation methods and model-scoring-based hyperparameter tuning to address the problem of class disproportionality, a common challenge in medical datasets and often the reason behind poor event prediction rate of various predictive models reported so far. …”

Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…The removal efficiencies in the proposed ENR-BP were four fold higher than the suspended growth process and in the same order of magnitude of 5-stage Bardenpho-MBBR. The developed ANN-based model provides an efficient and robust tool for predicting and forecasting the performance of the ENR-BP.…”

Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

“…Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”

An intelligent approach to predicting the effect of nanoparticle mixture ratio, concentration and temperature on thermal conductivity of hybrid nanofluids by Ifeoluwa Wole-Osho (14151315)

Electrical efficiency of the photovoltaic/thermal collectors cooled by nanofluids: Machine learning simulation and optimization by evolutionary algorithm by Yan Cao (482880)

Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm by Khadija Attouri (18024307)

“…<p>This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. …”

Properties of Unique Degree Sequences of 3-Uniform Hypergraphs by Tarsissi, Lama

“…The existence of this hypergraph makes us conjecture an extended generating algorithm for the sequences of Deza et al. to include a much wider class of unique 3-uniform hypergraphs. …”
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Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test by Hasan T. Abbas (8115014)

“…Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. All possible combinations of the 10 best ranked features were used to generate SVM based prediction models. …”

Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

“…We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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A control algorithm to increase the efficient operation of wind energy conversion systems under extreme wind conditions by Nyam Jargalsaikhan (17380429)

“…<p dir="ltr">This paper aims to increase the power production of gearless permanent magnet synchronous generator (PMSG) based wind energy conversion systems (WECS) in strong (greater than 25 m/s) wind speed regions. …”

Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine by Shomope, Ibrahim

“…The type of algorithm employed to predict drug release from liposomes plays an important role in affecting the accuracy. …”
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Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

“…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. …”

IoT-Based Sustainable Parking Lot by Binmahfooz, Abdullah

“…Furthermore, deep learning neural network was used to predict the congestion of the parking lot at any day or time. …”
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Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks by Haris M. Khalid (17017743)

Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben Romdhane, Haifa

“…The validation of these results was performed using previous archaeological works as well as geological and geomorphological field surveys. The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben-Romdhane, Haïfa

“…The validation of these results was performed using previous archaeological works as well as geological and geomorphological field surveys. The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…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. …”

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

“…Three different publicly available datasets have been used based on the age group to create the best predicting model for each case. …”