neural network tool (MathWorks Inc)
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90
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MathWorks Inc
neural network tool
Neural Network Tool, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/network+tool/us12368288-82-5-5
Average 90 stars, based on 1 article reviews
Neural Network Tool, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/network+tool/us12368288-82-5-5
Average 90 stars, based on 1 article reviews
neural network tool - by Bioz Stars,
2026-11
90/100 stars
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Software:Article Title: Metaheuristics Algorithm-Based Optimization for High Conductivity and Hardness CuNi 2 Si 1 Alloy. Article Snippet: .. Implementation of the model involved use of the MATLAB Article Title: Optimization of Millet Malting Parameters Using Artificial Neural Network and Response Surface Methodology Article Snippet: .. To determine the optimal neural network, the Article Title: Synergistic coupling of ultrasonic cavitation with tailored deep eutectic solvent systems for intensified extraction of Scutellaria Radix flavonoids: Modelling and optimization by genetic algorithm Article Snippet: .. In this study, a backpropagation algorithm combined with the Levenberg–Marquardt (LM) algorithm was utilized to develop a multilayer perceptron (MLP) architecture for a feed-forward neural network, implemented in Construct:Article Title: GIS mechanical fault diagnosis method and device Article Snippet: .. In a specific embodiment, the Article Title: Surrogate-based approach of predicting and optimising building performance by integrating daylighting, thermal comfort, and costs - A case study of community care homes Article Snippet: Given the unprecedented growth of the ageing population and the unique demands on indoor environments, enhancing the performance of community care homes (CCHs) is essential to ensuring the health and well-being of older adults.. However, in designing CCHs, performance criteria from conventional public buildings are often employed as reference indicators (RIs), overlooking age-friendly indicators (AFIs) and offering limited exploration of integrated performance design.. Thus, this research proposes a surrogate-based multi-objective optimisation (MOO) approach for the early design stage of CCHs, aiming to maximise daylighting and thermal comfort while minimising costs, with age-friendly indicators including sDA750,50%, ASE1000,250h, wPMV0.5, sPMV0.5, and Cost. Activation Assay:Article Title: Surrogate-based approach of predicting and optimising building performance by integrating daylighting, thermal comfort, and costs - A case study of community care homes Article Snippet: Given the unprecedented growth of the ageing population and the unique demands on indoor environments, enhancing the performance of community care homes (CCHs) is essential to ensuring the health and well-being of older adults.. However, in designing CCHs, performance criteria from conventional public buildings are often employed as reference indicators (RIs), overlooking age-friendly indicators (AFIs) and offering limited exploration of integrated performance design.. Thus, this research proposes a surrogate-based multi-objective optimisation (MOO) approach for the early design stage of CCHs, aiming to maximise daylighting and thermal comfort while minimising costs, with age-friendly indicators including sDA750,50%, ASE1000,250h, wPMV0.5, sPMV0.5, and Cost. other:Article Title: MobileTurkerNeXt: investigating the detection of Bankart and SLAP lesions using magnetic resonance images. Article Snippet: The landscape of computer vision is predominantly shaped by two groundbreaking methodologies: transformers and convolutional neural networks (CNNs).. In this study, we aim to introduce an innovative mobile CNN architecture designed for orthopedic imaging that efficiently identifies both Bankart and SLAP lesions.. Our approach involved the collection of two distinct magnetic resonance (MR) image datasets, with the primary goal of automating the detection of Bankart and SLAP lesions. |
