BP and PSO-based data prediction method, system and related apparatus

Abstract

The invention discloses a BP and PSO-based data prediction method. An inertial factor periodic change formula is constructed to quickly adapt to periodically changed particle positions; the size of aninertial factor and another inertial factor dynamic change formula are determined; a running state of PSO particles in a previous iterative period is reflected by utilizing an evolution degree value;the degree of evolution in speed is reflected; the characteristics of aggregation are reflected by utilizing an aggregation degree value; the PSO particles are enabled to be in a dynamic update statethrough two dynamic variables; and the inertial factor is adjusted. Double strategies for changing the inertial factor in a mixed way are adopted; inevitable oscillation and divergent characteristicsof PSO and BP are fully considered; the value of the inertial factor is continuously modified; and the prediction precision and the convergence speed can be greatly improved. Meanwhile, the inventionfurthermore discloses a BP and PSO-based data prediction system and apparatus, and a computer readable storage medium, which have the abovementioned beneficial effects.

Description

technical field [0001] The present application relates to the technical field of data prediction, and in particular to a data prediction method, system, device and computer-readable storage medium based on BP and PSO. Background technique [0002] Load forecasting is an important content in economic dispatching of power system and an important module of energy management system (EMS). Power system load forecasting refers to the research and use of a set of mathematical methods for dealing with past and future loads under the conditions of fully considering system operating characteristics, capacity increase decisions, natural conditions, and social influences. On the basis of meeting certain accuracy requirements, Predict the load value at a specific time in the future. Improving the level of load forecasting technology is conducive to planning power consumption management, rationally arranging power grid operation mode and unit maintenance plan, helping to save coal, oil a...

AI Technical Summary

Problems solved by technology

Although this method can obtain a better network structure and a generalized population, the population size still cannot avoid the defects of PSO and BP itself, and oscillation and divergence will still occur, that is to say, it is still to find in the non-optimal population. best effect

At the same time, when oscillating and diverging or encountering special values, the average value is still used to calculate, abandoning the particularity of the parameters, and the actual prediction effect is not good

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