BiLSTM-Attention Prediction Model and Error Analysis #br#
Based on Novel Multi-objective Coati Optimization Algorithm

doi:10.3969/j.issn.1006-2475.2024.11.011

Abstract

Abstract: Project cost prediction plays an important role in modern project management. However， due to market fluctuations， labor costs， and other factors， project cost forecasting has been challenging. Therefore， a novel multi-objective coati optimization algorithm is proposed， and a bidirectional long short-term memory network （BiLSTM） and attention mechanism optimized based on this algorithm are proposed to predict the cost of substation engineering. Firstly， the proposed algorithm is compared with the mainstream multi-objective optimization algorithm on 8 test problems， and the effectiveness of the multi-objective coati optimization algorithm is verified. Secondly， the proposed algorithm is used to optimize the prediction model to improve the accuracy of the model. The BiLSTM-Attention model captures the potential relationship in historical data to improve the accuracy and reliability of power transformation project cost prediction. Finally， the proposed model is compared with the five mainstream models， and the historical data of a 110 kV power transformation project in a province is used as a case study. The results show that the average absolute percentage error of the proposed model is 3.71%， which is reduced by 9.82 percentage points compared with BP， 5.81 percentage points compared with ANN， 5.40 percentage points compared with LSTM， 2.03 percentage points compared with LSTM-SVR， and 1.00 percentage points compared with CNN-LSTM.

Key words: engineering cost, multi-objective coati optimization algorithm, BiLSTM, attention mechanism, prediction ,

CLC Number:

TM73
TP183

LI Junchao1, YOU Fei1, ZHANG Chao2, SU Lele2, GONG Yan2 . BiLSTM-Attention Prediction Model and Error Analysis #br# Based on Novel Multi-objective Coati Optimization Algorithm[J]. Computer and Modernization, 2024, 0(11): 70-76.

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BiLSTM-Attention Prediction Model and Error Analysis #br# Based on Novel Multi-objective Coati Optimization Algorithm

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