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121
Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…Therefore, early and accurate diagnosis and classification of breast lesions into malignant or benign lesions is an active domain of research. Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…This work identifies the most reliable machine learning (ML) strategies for forecasting corrosion inhibitor efficiency before synthesis, thereby shortening development cycles and reducing experimental cost. Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”
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PILE-UP FREE PARAMETER ESTIMATION AND DIGITAL ONLINE PEAK LOCALIZATION ALGORITHMS FOR GAMMA RAY SPECTROSCOPY
Published 2020“…A number of parameter estimation and digital online peak localisation algorithms are being developed, including a pulse classification technique which uses a simple peak search routine based on the smoothed first derivative method, which gave a percentage error of peak amplitude of less than 0.1. …”
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130
Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions
Published 2017“…For this purpose, computer programs based on updated pattern recognition algorithms were developed for joint-detection and classification of rock types to offer an estimated strength. …”
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Optimization of PV Cleaning Practices: Comparison Between Performance-Based and Periodic-Based Approaches
Published 2020“…It is important to choose the right cleaning strategy (method and frequency) to maximize the electricity production and economic performance of the PV facility. An optimization algorithm was developed and tested for multiple PV panel configurations based in Dubai Water and Electricity Authority’s (DEWA) outdoor test facil ity (OTF) solar lab. …”
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Optimisation of PV Cleaning Practices: Comparison Between Performance Based and Periodic Based Approaches
Published 2018“…To optimize the cleaning practices, an algorithm was developed by the author based on the literature review and economic analysis, and was run for multiple panels and tilts at the DEWA OTF solar lab in Dubai, UAE. …”
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Towards Scalable Process Mining Pipelines
Published 2023“…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …”
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…The model aims to compare the performance of classical perturb and observe (P&O) algorithm, particle swarm optimization (PSO) algorithm, flower pollination algorithm (FPA), and SMC-based tracking techniques. …”
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Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm
Published 2023“…The standard ARO algorithm is developed to mimic the foraging behavior of rabbits, and in this work, the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight technique. …”
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A localized navigation algorithm for radiation evasion for nuclear facilities: Optimizing the "Radiation Evasion" criterion: Part I
Published 2013“…When used to navigate based on local radiation information, the algorithm will behave more reliably when accidents happen, since no long-haul communication links are required for information exchange. …”
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Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
Published 2020“…<p dir="ltr">The number of Internet of Things (IoT) devices is growing at a fast pace in smart homes, producing large amounts of data, which are mostly transferred over wireless communication channels. …”
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