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transfer functions tansig, purelin, and logsig  (MathWorks Inc)


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    MathWorks Inc transfer functions tansig, purelin, and logsig
    Properties of ANN Models
    Transfer Functions Tansig, Purelin, And Logsig, 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/logsig+transfer+function/pmc10702175-306-6-16
    Average 90 stars, based on 1 article reviews
    transfer functions tansig, purelin, and logsig - by Bioz Stars, 2026-10
    90/100 stars

    Images

    1) Product Images from "Artificial Neural Network Approach for Modeling of Effect of Ultrasound on the Dissolution of Magnesia in Aqueous Carbon Dioxide"

    Article Title: Artificial Neural Network Approach for Modeling of Effect of Ultrasound on the Dissolution of Magnesia in Aqueous Carbon Dioxide

    Journal: ACS Omega

    doi: 10.1021/acsomega.3c03668

    Properties of ANN Models
    Figure Legend Snippet: Properties of ANN Models

    Techniques Used: Biomarker Discovery

    Related Articles

    other:

    Article Title: Investigation Of Infrared Drying Behaviour Of Spinach Leaves Using ANN Methodology And Dried Product Quality
    Article Snippet: Logsig transfer function was calculated for a layer’s output from its net input (The Mathworks Inc., 2009).

    Article Title: Modeling Microwave Drying Kinetics of Thyme (Thymus Vulgaris L.) Leaves Using ANN Methodology and Dried Product Quality
    Article Snippet: Effects of microwave power output and sample mass on drying behavior, color parameters, rehydration characteristics and some sensory scores of thyme leaves were investigated.. Within the range of the microwave power outputs, 180–900 W, and sample amounts, 25–100 g, moisture content of the leaves were reduced to 0.1 (0.01) from 4.05 kg water/kg dry base value.. Drying times of the leaves were found to be varying between 3.5 and 15.5 min for constant sample amount, and 6.5 and 20.5 min for constant power output.

    Article Title: Artificial neural network model for desalination by sweeping gas membrane distillation
    Article Snippet: A net input argument b bias term for a neuron b bias vector for a layer E error function J distillate (permeate) flux IW input weight matrix logsig log-sigmoid transfer function (Matlab syntax) LW layer weight matrix MSE mean-squared-error (performance function) n number of input variables N total number of experimental trials m number of artificial neurons PRN pseudo random number purelin linear transfer function (Matlab syntax) r2 linear correlation coefficient RF rejection factor Ta,in air inlet temperature Tf,in liquid inlet temperature ΔT temperature difference tansig hyperbolic tangent sigmoid transfer function (Matlab syntax) Ua air circulation velocity Uw liquid circulation velocity w weight (neural network connection) x vector of normalized input variables x normalized input variable Y performance index (experimental value/target) Ŷ performance index (predicted value/network output) Yn normalized performance index Ŷn vector of network output (normalized predicted values of performance index) z actual variable Subscripts and Superscripts exp experimental value i positive integer number (iteration index) j positive integer number (iteration index) k positive integer number (iteration index) max maximal level min minimal level pred predicted value q positive integer number (iteration index)

    Plasmid Preparation:

    Article Title: Artificial neural network modeling and response surface methodology of desalination by reverse osmosis
    Article Snippet: Response surface methodology (RSM) and artificial neural network (ANN) have been used to develop predictive models for simulation and optimization of reverse osmosis (RO) desalination process.. Sodium chloride aqueous solutions were employed as model solutions for a RO pilot plant applying polyamide thin film composite membrane, in spiral wound configuration.. The input variables were sodium chloride concentration in feed solution, C, feed temperature, T, feed flow-rate, Q, and operating hydrostatic pressure, P. The RO performance index, which is defined as the salt rejection factor times the permeate flux, has been considered as response.

    Concentration Assay:

    Article Title: Artificial neural network modeling and response surface methodology of desalination by reverse osmosis
    Article Snippet: Response surface methodology (RSM) and artificial neural network (ANN) have been used to develop predictive models for simulation and optimization of reverse osmosis (RO) desalination process.. Sodium chloride aqueous solutions were employed as model solutions for a RO pilot plant applying polyamide thin film composite membrane, in spiral wound configuration.. The input variables were sodium chloride concentration in feed solution, C, feed temperature, T, feed flow-rate, Q, and operating hydrostatic pressure, P. The RO performance index, which is defined as the salt rejection factor times the permeate flux, has been considered as response.

    Significance Assay:

    Article Title: Artificial neural network modeling and response surface methodology of desalination by reverse osmosis
    Article Snippet: Response surface methodology (RSM) and artificial neural network (ANN) have been used to develop predictive models for simulation and optimization of reverse osmosis (RO) desalination process.. Sodium chloride aqueous solutions were employed as model solutions for a RO pilot plant applying polyamide thin film composite membrane, in spiral wound configuration.. The input variables were sodium chloride concentration in feed solution, C, feed temperature, T, feed flow-rate, Q, and operating hydrostatic pressure, P. The RO performance index, which is defined as the salt rejection factor times the permeate flux, has been considered as response.



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    Image Search Results


    Properties of ANN Models

    Journal: ACS Omega

    Article Title: Artificial Neural Network Approach for Modeling of Effect of Ultrasound on the Dissolution of Magnesia in Aqueous Carbon Dioxide

    doi: 10.1021/acsomega.3c03668

    Figure Lengend Snippet: Properties of ANN Models

    Article Snippet: As transfer functions, TANSIG, PURELIN, and LOGSIG, transfer functions in the neural network toolbox in the matlab software program, were used.

    Techniques: Biomarker Discovery