About RAMPCO

We use Regression for finding a function that can relate system inputs to its outputs. There are some ML-based algorithms for the regression task. The most popular is the Artificial Neural Network (ANN).

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What is RAMPCO

We offer data segmentation so that the right professionals in the company manages the right components. We clean up the raw data putting it in standardized formats, then aggregate, de-identify, pool, and mine for insights. This identifies the roles each data engineer and AI personnel should play, both in our team and also at the clients front at different points on the process chain.

Firstly, we use the major part of the initial data (e.g., 80 %) for training ML and a minor component for testing the network. If the error (the difference between the network output and the real values) on the test data is acceptable, we use the trained system as a model for future predictions; otherwise, it should be re-trained by new training parameters.

Secondly, when the model is ready, we use an optimization algorithm such as the Metaheuristic Genetic Algorithm (GA) to search inside the model aiming to find appropriate input values to gain the best output values. The GA completes the internal search in conjunction with the programmed interface. This mechanism is applicable for optimizing every production line from steel /iron production to the petrochemical and automotive industry and chemical production industry. Our prototype in the Business Plan covers the Chemical Production Industry. The overall package algorithm is implemented in the form of an industrial software that uses a cloud service model: the suite containing ANN (feed-forward), Genetic Algorithm, and interface.

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Today Most of High Tech Companies are Using AI and ML

AI and Machine Learning can be best applied to any actual business situation. It means that the market is limitless, provided that quality Data Professionals are in abundant supply. Increasing plant automation is projected to drive the product optimization software market in the coming years. (Transparency Market Research). Big Data can convert a large chunk of industry data into supportive analysis so that Companies can improve making the right decisions and improve industrial plant operations. However, data regulations and standards are likely to hinder the product optimization software market.

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