A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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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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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

“…Distributed clustering algorithms, however, can fulfil this gap. They extract a classification model from the distributed objects even when they are in different sites and locations. …”
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A distributed genetic algorithm for deterministic and stochastic labor scheduling problems by Mansour, Nashat

“…Our distributed genetic algorithm operates in parallel on a network of message-passing workstations. …”
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Distributed DRL-Based Downlink Power Allocation for Hybrid RF/VLC Networks by Bekir Sait Ciftler (17541801)

“…We implement a simulation environment to benchmark the proposed distributed DRL-based method against other methods such as Q-Learning (QL) and Deep Q-Networks (DQN), and centralized heuristic power allocation algorithms. …”

Natural optimization algorithms for the cross-dock door assignment problem by Tarhini, Abbas A.

“…This paper modifies a classical mathematical model that represents the CDAP and implements an evolutionary metaheuristic SS algorithm and tests it and then compares the results with those of another evolutionary algorithm, i.e., genetic algorithm (GA). …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

“…After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”

A family of minimum curvature variable-methods for unconstrained optimization. (c1998) by Obeid, Samir Y.

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Active distribution network type identification method of high proportion new energy power system based on source-load matching by Qinlin, Shi

“…Here, we report an active distribution network type identification method based on source-load matching. Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …”
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars by Abathar Al-Hamrani (16494884)

“…A 3D finite element model was first developed and validated against available experimental results. …”

A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance by Krishnamoorthy Natarajan (22047464)

Cortical EEG Source Localization of Focal Epilepsy by Siyam, Wisal Elfatih Mohamed

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A quantum algorithm for evolving open quantum dynamics on quantum computing devices by Zixuan Hu (13719685)

“…<p dir="ltr">Designing quantum algorithms for simulating quantum systems has seen enormous progress, yet few studies have been done to develop quantum algorithms for open quantum dynamics despite its importance in modeling the system-environment interaction found in most realistic physical models. …”

Fragment based protein structure prediction. (c2013) by Terzian, Meghrig Ohanes

“…In addition, it demonstrates the advantage of using the CHARMM36 energy model. The method is based on a two-phase Scatter Search metaheuristic that minimizes the energy function. …”
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Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems by Abualigah, Laith

“…The proposed method is based on enhancing the search process of the Prairie Dog Optimization Algorithm (PDOA) by using the primary updating mechanism of the Dwarf Mongoose Optimization Algorithm (DMOA). …”
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An enhanced consensus-based distributed secondary control for voltage regulation and proper current sharing in a DC islanded microgrid by Nada Mosaad (21633245)

A Comprehensive Review on Conventional and Machine Learning-Assisted Design of 5G Microstrip Patch Antenna by Nupur Chhaule (21224987)

Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

“…Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.…”

Regulating algorithmic care in the European Union: evolving doctor–patient models through the Artificial Intelligence Act (AI-Act) and the liability directives by Barry Solaiman (19160614)

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. …”