2 results about "Big data cloud computing" patented technology

This invention discloses an intelligent analysis and decision-making system for agricultural finance using big data and cloud computing, belonging to the interdisciplinary field of agricultural finance and big data / cloud computing. The system includes a data acquisition module, a data preprocessing module, a cloud computing processing module, an intelligent analysis module, a decision generation module, a data storage module, a feedback optimization module, and an interactive display module. These modules work together to form a closed-loop process. The data acquisition module collects multi-dimensional data from the entire agricultural industry chain; the data preprocessing module constructs standardized datasets; the cloud computing processing module achieves efficient processing of massive amounts of data; the intelligent analysis module uses proprietary deep learning algorithms for multi-dimensional analysis; the decision generation module generates personalized decision-making solutions; and the feedback optimization module achieves adaptive optimization of the model and rules. This invention offers comprehensive data coverage, high processing efficiency, high analytical accuracy, and intelligent decision-making, overcoming the shortcomings of existing technologies and can be widely applied to various agricultural finance scenarios.

A closed-loop joint design method for power batteries and their battery management systems is proposed. This method utilizes big data cloud computing and combines digital modeling and parameter joint evaluation and updating to achieve a high-quality closed-loop optimization design that organically integrates power battery design and battery management system design. Through a "know-before-building" approach, a battery with "know-before-testing" capabilities is ultimately obtained. A complete parameter set for the battery to be designed is formed by combining big data cloud computing and battery design parameters. Simulation experiments are then conducted to obtain matching battery characteristic responses, which are used for modeling and developing management algorithms for the battery management system. This results in the manufacture of a digital battery with optimal performance and management indicators, which is then materialized to design a high-performance, well-managed "new battery," achieving the goal of "building for use."