Adaptive decision model of product team organization pattern for extracting new energy from agricultural waste

Abstract

The objective of this work is to solve the low efficiency in the extraction of new energy from Agricultural Waste (AW). In this work, the development and utilization of AW are discussed in depth by combining with the current technological progress. To effectively implement new energy mining projects, the adaptive decision model of product team organization pattern is studied deeply, and the Fuzzy Neural Network (FNN) model is mainly used as the decision method to select product team organization pattern. The biomass waste is solidified and formed as fuel. The principle is to crush biomass waste to a certain extent and compress it into rod or block by physical extrusion. During training of the FNN, each parameter needs to be constantly adjusted to make the new data reach the target value fitting output value as far as possible after passing the FNN. The test results show that the FNN has achieved satisfactory prediction results in 18 groups of test data. The point structure entropy and edge structure entropy of product innovation service team are −1.931 and 0.09 respectively. To sum up, extracting new energy from AW can realize sustainable development of society. The adaptive decision model based on product team organization pattern can complete the effective connection of energy product constituent entities, provide technical support for the maximum utilization of social service resources, and promote the extraction and utilization of new energy more efficiently.