Bank outlet workload prediction method and device, electronic equipment and storage medium

Abstract

The invention provides a bank outlet workload prediction method and device, electronic equipment and a storage medium. The method comprises the steps: obtaining workload flow data and auxiliary data of a bank outlet; performing feature extraction according to the workload flow data and the auxiliary data to obtain feature data; respectively inputting the feature data into a plurality of pre-trained monomer prediction models to obtain corresponding prediction values; adopting a non-dominated sorting genetic algorithm with an elitist strategy to process the prediction value of each monomer prediction model to obtain a bank outlet workload prediction result, wherein the monomer prediction model is a holt-works model, a multi-layer perceptron model, a decision tree model, a gradient boosting tree regression model and a long short-term memory network model. According to the invention, the method can efficiently and accurately predict the workload of each post of the outlet every day in a future period of time, and guide the bank outlet to determine the number of workers required by each post.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a method and device for predicting the workload of a bank outlet, electronic equipment and a storage medium. Background technique [0002] A bank outlet is a place where a bank operates externally, and is generally divided into branches, sub-branches, sub-branches, savings offices, etc. In order to effectively provide customers with high-quality services, it is necessary to accurately predict the workload of bank outlets and reasonably schedule staff at outlets, so as to realize the optimization of outlet positions and labor mix and the optimal allocation of customer services. [0003] The traditional bank outlets forecast the transaction volume and workload of each position in the outlet, usually based on the experience of business personnel and manual statistics of historical transaction data, and then further guide the scheduling of each position in the outlet ...

AI Technical Summary

Problems solved by technology

Since the transaction volume of outlets is affected by the economic environment and the surrounding human environment, including changes in the external environment, national holidays, and major events, etc., the memory and judgment of business personnel will cause large deviations, resulting in the allocation of human resources in outlets. Surplus or deficiency, which increases the operating cost of the bank

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