Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”

Nonlinear model predictive control of Hammerstein and Wiener modelsusing genetic algorithms by Al-Duwaish, H.

“…In this paper a novel approach for the implementation of nonlinear MPC is proposed using genetic algorithms (GAs). The proposed method formulates the MPC as an optimization problem and genetic algorithms are used in the optimization process. …”
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An Ultrafast Maximum Power Point Setting Scheme for Photovoltaic Arrays Using Model Parameter Identification by Zhaohui Cen (17217391)

Improved search-tree algorithms for the cluster edit problem. (c2011) by Ghrayeb, Ali Kassem

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On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise by Saab, Samer S.

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A machine learning model for early detection of diabetic foot using thermogram images by Amith Khandakar (14151981)

“…A comparatively shallow CNN model, MobilenetV2 achieved an F1 score of ∼95% for a two-feet thermogram image-based classification and the AdaBoost Classifier used 10 features and achieved an F1 score of 97%. …”

Use of Data Mining Techniques to Detect Fraud in Procurement Sector by AL HAMMADI, SUMAYYA ABDULLA

“…The method used in this research is a classification of models and algorithms used in data mining. …”
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A method for the minimum coloring problem using genetic algorithms by Harmanani, Haidar

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Economic load dispatch using memetic sine cosine algorithm by Abu Zitar, Raed

“…In this paper, the economic load dispatch (ELD) problem which is an important problem in electrical engineering is tackled using a hybrid sine cosine algorithm (SCA) in a form of memetic technique. …”
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A data envelopment analysis model for opinion leaders’ identification in social networks by Hamed Baziyad (19273738)

“…Social Network Analysis (SNA)-based OLs finding methods deal with a considerable amount of data due to using entire relationships between all of the users in a network, which makes the algorithms time-consuming. …”

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

“…This paper explores the calculation of European option prices on energy futures using a time-varying volatility model enhanced by a regime switching factor. …”
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Integrated economic and environmental models for a multi stage cold supply chain under carbon tax regulation by Hariga, Moncer

“…The structural properties for the optimal solution of the three models are identified and solution algorithms are also proposed. …”
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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 aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. …”

Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications by Estahbanati, Shahabeddin Vamegh

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Brain Source Localization in the Presence of Leadfield Perturbations by Momin, Rabiya Nakhat

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

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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

“…The data forecasting horizon used was a 24-h window in steps of 30 min. We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. …”

A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs† by Harmanani, Haidar

“…This paper presents a hardware implementation to solve the graph colouring problem (chromatic number χ(G)) for arbitrary graphs using the Hopfield neural network (HNN) model of computation. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”