Optimizing photovoltaic parameters with Monte Carlo and parallel resistance adjustment by Fatima Wardi, Mohamed Louzazni, Mohamed Hanine, Elhadi Baghaz, Sanjeevikumar Padmanaban

“…In the end, to evaluate the algorithm’s effectiveness, statistical measurements such as Individual Absolute Error (IAE), Relative Error (RE), Mean Absolute Error (MAE), SD, TS, NFM, ACF, and RMSE are calculated to ensure the correctness of the generated parameters. …”
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Brain-Shapelet: A Framework for Capturing Instantaneous Abnormalities in Brain Activity for Autism Spectrum Disorder Diagnosis by Yijie Ren, Zhengwang Xia, Yudong Zhang, Zhuqing Jiao

“…It applies random walk algorithm on group-representative brain network to obtain brain region sets, and aggregates their blood oxygen level-dependent (BOLD) signals to extract Shapelets that reflect the associations between different brain regions at the same time point. …”
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Application and feasibility analysis of knowledge-based machine learning in predicting fatigue performance of stainless steel by Jia Wang, Dongkui Fan, C.S. Cai

“…To better predict the fatigue-related S-N curves of different series of stainless steels, 570 sets of data including fatigue test results and other performance parameters for five common types of stainless steel materials were initially collected. …”
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Design and Assessment of an Austenitic Stainless Alloy for Laser Powder Bed Additive Manufacturing by Mariam Assi, Julien Favre, Marcin Brykala, Franck Tancret, Anna Fraczkiewicz

“…The microstructure and mechanical properties of the alloys are evaluated and its printability is compared with a commercial 316L stainless steel taken as a reference. …”
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Optimizing energy cost in the residential sector through home energy management systems in a smart grid environment by Nabeeha Qayyum, Umar Jamil, Anzar Mahmood

“…This research aims to optimize power usage by reducing peak loads and electricity costs through the integration of RESs, such as solar or photovoltaic (PV) systems, while considering grid limitations, PV capacity, appliance ON/OFF schedules, and time-of-use tariffs. A genetic algorithm (GA) based optimization technique was employed to evaluate the performance of a HEMS and validated with particle swarm optimization (PSO) technique under identical initial conditions for each appliance and their corresponding energy pricing over different periods. …”
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Digital fundus image quality assessment by V. V. Starovoitov, Y. I. Golub, M. M. Lukashevich

“…For this, a new universal retinal image binarization algorithm is proposed. By analyzing result of the binarization, it is possible to identify and remove imagesoutliers, which show not the retina, but other objects. …”
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BAYESIAN ESTIMATE OF TELECOMMUNICATION SYSTEMS PREPAREDNESS by V. E. Emelyanov, S. P. Matyuk

“…The parameters of the a priori information can be determined by different methods or on the basis of sufficient statistical data. …”
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A Multidimensional Analysis Approach Toward Sea Cliff Erosion Forecasting by Maria Krivova, Michael J. Olsen, Ben A. Leshchinsky

“…This study presents an innovative Geographic Information Systems (GIS) algorithm to forecast sea cliff erosion progression utilizing imagery datasets (hereafter referred to as ‘rasters’). …”
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Deterring Street Crimes Using Aerial Police: Data-Driven Joint Station Deployment and Patrol Path Planning for Policing UAVs by Zuyu Chen, Yan Liu, Shengze Hu, Xin Zhang, Yan Pan

“…Evolved from the path planning algorithm, the second module utilizes a data-driven method to estimate the deterring effect of the candidate UAV stations with different numbers of UAVs. …”
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Strategic Traffic Management in Mixed Traffic Road Networks: A Methodological Approach Integrating Game Theory, Bilevel Optimization, and C-ITS by Areti Kotsi, Ioannis Politis, Evangelos Mitsakis

“…The methodology includes defining a model to achieve optimal mixed equilibria, designing an algorithm for multiclass traffic assignment, formulating strategic games to analyze player interactions, and establishing key performance indicators to evaluate network efficiency and effectiveness. …”
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Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

“…crops, different weeds grow along with potatoes in agricultural fields. …”
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Classification of English Words into Grammatical Notations Using Deep Learning Technique by Muhammad Imran, Sajjad Hussain Qureshi, Abrar Hussain Qureshi, Norah Almusharraf

“…This situation stresses the need to develop a computer-based system using a machine learning algorithm to classify words into proper grammatical notations. …”
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Methodology for classification of land use and vegetation cover using MODIS-EVI data by Vagner P. Mengue, Denise C. Fontana, Tatiana S. da Silva, Daniel Zanotta, Fernando C. Scottá

“…The procedures included the use of MODIS Sensor images, altimetric data and nighttime images, associated with a hierarchical decision tree classifier, constructed using the C4.5 algorithm. The proposed approach stems from the consideration that the study area has varying characteristics and, therefore, should be treated simultaneously by different and intuitive classifiers, which justifies the choice of decision tree. …”
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HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis by Dawit Kefale Wassie, Lebsework Negash Lemma, Abrham Tadesse Kassie

“…The study of the control of quadrotors was addressed extensively in different AAV research areas. In this work, the nonlinear dynamic model of the quadrotor has been developed using the Newton-Euler technique. …”
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Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation by S. Rashmi, S. Srinath, R. Rakshitha, B. V. Poornima

“…The combination of the single model and multi-model approach with UNet and UNetPlusPlus results in four base learners, each displaying varying accuracy for different landmarks. To leverage the strengths of these individual models, three ensemble methods are explored, that includes supervised ensembling with XGBoost, unsupervised ensembling with the DBSCAN algorithm, and mathematical aggregation using weighted averaging. …”
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Optimal design of a hybrid system composed of coagulation process and multi-stage filtration unit for on-site treatment of greywater in rural area by Zahra Akbari, Fereshteh Nourmohammadi Dehbalaei, Zahra Mohammad Hosseini, Seyed Taghi Omid Naeeni

“…Multilayer nonlinear machine learning model was utilized to evaluate the performance of this hybrid system and adaptive heuristic search algorithm was used to achieve the optimal configuration of multilayer sand filter using optimization technique. …”
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Development of An Optimal Low-Noise Voice-Coil Actuator for Precision Motion Control Applications by Suorena Saeedi, Ali Sadighi, Masoud Shariat Panahi

“…Finally, the effectiveness of the multi-physics-based modeling approach, enhanced by experimentally-driven characteristics, is evaluated against empirical results.…”
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Universal Modeling for Non-Destructive Testing of Soluble Solids Content in Multi-Variety Blueberries Based on Hyperspectral Imaging Technology by Lingqi Meng, Guoliang Chen, Dayang Liu, Ning Tian

“…The characteristic wavelengths were optimized in stages by uninformative variables elimination (UVE) and the successive projections algorithm (SPA), and the model was simplified by multiple linear regression (MLR). …”
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Low-Field Magnetic Resonance Imaging: A Full-Wave Simulation of Radiofrequency Birdcage Coils for Musculoskeletal Limb Imaging by Giulio Giovannetti, Francesca Frijia, Maria Filomena Santarelli, Vincenzo Positano

“…<b>Methods:</b> This paper describes the application of a numerical full-wave method based on the finite-difference time-domain (FDTD) algorithm for the simulation and the design of birdcage coils for musculoskeletal low-field MRI. …”
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Machine learning based shear strength prediction in reinforced concrete beams using Levy flight enhanced decision trees by Aybike Özyüksel Çiftçioğlu, Anıl Delikanlı, Torkan Shafighfard, Faramarz Bagherzadeh

“…A comprehensive dataset comprising 195 experimentally tested T-beams is used to train and evaluate six different regression models, including optimized Decision Tree, Random Forest, AdaBoost, K-Nearest Neighbors, Ridge Regression, and the proposed Levy-DT. …”
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