matlab v.2015 (MathWorks Inc)
Structured Review
Matlab V.2015, 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/matlab+v%2E2015/10__1007_slash_s42979___024___02742___3-110-7-0
Average 90 stars, based on 1 article reviews
Images
Related Articles
other:Article Title: Novel, non-invasive imaging approach to identify patients with advanced non-small cell lung cancer at risk of hyperprogressive disease with immune checkpoint blockade Article Snippet: The statistical analysis was performed using Article Title: Performance optimization of integrated resilience engineering and lean production principles Article Snippet: Article Title: Design of Chest Visual Based Image Reclamation Method Using Dual Tree Complex Wavelet Transform and Edge Preservation Smoothing Algorithm Article Snippet: Matlab v.2015 (a) is the chosen software tool for implementing this framework. Article Title: Evolving multilayer perceptron, and factorial design for modelling and optimization of dye decomposition by bio-synthetized nano CdS-diatomite composite. Article Snippet: This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record.. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article.. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Article Title: Hybrid PSO enhanced ANN model and central composite design for modelling and optimization of Low-Intensity magnetic separation of hematite Article Snippet: The low intensity dry magnetic beneficiation of hematite was studied in this study, and the effect of field intensity (FI: 800–2000 G), drum speed (DS: 25–75 rpm), separating gate position (SG: 55–83), and mean particle size (PS: 0.5–1.18 mm) on the products’ Fe content and system separation efficiency were determined.. A new hybrid particle swarm optimization enhanced multilayer perceptron (PSO-MLP) neural network and design of experiment have been employed to model and predict such a beneficiation result.. Based on the CCD-RSM response surfaces, the effectiveness of variables on both evaluation criteria was determined to be DS > FI > SG. |
