Equipment consumption prediction based on CNN-LSTM

Equipment demand prediction is the basic work of equipment protection, and it has traction for equipment financing and replenishment. Using CNN-LSTM model, a prediction model of factors affecting equipment consumption such as operation duration, operation task, operation intensity, number of personnel, participating equipment index, climate, terrain, wind, visibility, etc. is established, and experiments show that the model has high prediction accuracy and solves the problem of poor prediction accuracy in the past, which is of great significance for equipment protection. Experiments show that the model has high prediction accuracy and solves the previous problem of low prediction accuracy by using only historical data and traditional experience, which is of great significance to equipment security.