Study On Models Of Different Types Of Biomass Waste Anaerobic Digestion Gas Production Forecast

With the accelerated pace of urban development in China, the gradual improvement of living standards, solid waste generation is also growing fast, especially in the proportion of biomass waste. Biomass waste recycling relieves pressure on the environment and conserves energy.In this paper, for the digestion of different biomass gas production forecast, established multiple regression model and BP-ANN model.Based on fat matrix and mixed anaerobic sludge experiment, established multiple regression model,the average prediction accuracy is75.69%,79.29%; established BP-ANN models the average prediction accuracy is 79.05%. Prediction accuracy of two models are similar, the results of prediction is good.Based on high organic loading mixed food waste and anaerobic sludge, established multiple regression model,the average prediction accuracy is60.05%,22.21%; established BP-ANN models the average prediction accuracy is 72.40%. Obviously, BP-ANN models are better than multiple regression models.Based on soybean matrix and mixed anaerobic sludge experiment, established BP-ANN model, the average prediction accuracy is52.19%; Based on celery matrix and mixed anaerobic sludge experiment, established BP-ANN model, the average prediction accuracy is69.13%; based on low organic loading mixed food waste and anaerobic sludge, established BP-ANN model, the average prediction accuracy is 86.30%.It can be see, the average prediction accuracy of BP-ANN models always at a higher level,and stable.Conteasted two models, that it is feasible to use BP-ANN model in gas production forecast of mixed anaerobic digestion.BP-ANN model is superior to multiple regression model.In conclusion, the mixed anaerobic gas forecasting model based on BP-ANN built in this paper provided an operable and efficient method for production in the future.