Create a new novel operator function mathematically by modifying exiting model of CNN model.

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Dataset Example:

Assuming we have the following data:

• Longitude: [list of longitude values]

• Latitude: [list of latitude values]

• Categorical Data: [categorical data as list excel datafile]

• Physiochemical Components: [Excel containing PH, Alkalinity, Salinity, etc.]

Create a new operator function based on the Convolutional Neural Network (CNN) model that accepts spatial components such as longitude and latitude, in addition to categorical datasets. The target dataset is the Groundwater dataset, which consists of longitude and latitude coordinates along with categorical data, as well as physiochemical components of water such as pH, Alkalinity, Salinity, etc.

An example of the function creation is provided in the figure attached, which needs to be completed following the same.

Basic Task and idea:

Complete the numerical function mathematically that will show:

Spatial Input Operator:

• spatial_input_operator(longitude, latitude, categorical_data) as illustrated in the figure:

• Description: This operator takes in spatial components (longitude and latitude) along with categorical data and prepares the input for the CNN model.

Spatial Convolution Operator:

• spatial_convolution_operator is the ( modified operator that combine long & lat with Categorical sets):

• Description: This operator performs spatial convolution on the input data applying convolutional operations to capture spatial patterns + Categorical data.

Spatial Pooling Operator:

• spatial_pooling_operator from(convolved_data, pool_size, pooling_type):

• Description: This operator applies spatial pooling to the convolved data (modified operator).

Procesamiento de datos Machine Learning (ML) Deep Neural Network Matemáticas AI Model Development

Nº del proyecto: #37643922

Sobre el proyecto

12 propuestas Proyecto remoto Activo hace 3 meses

12 freelancers están ofertando un promedio de $53 por este trabajo

schoudhary1553

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