Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer models. Nature-inspired techniques are a recently developed branch of artificial intelligence wherein knowledge is transferred from natural systems to engineered systems. For soft computing applications, nature-inspired techniques have several advantages, including scope for parallel computing, dynamic behavior, and self-organization. This paper presents a comprehensive review of such techniques and their application in anaerobic digestion modeling. We compiled and synthetized the literature on the applications of nature-inspired techniques applied to anaerobic digestion. These techniques provide a balance between diversity and speed of arrival at the optimal solution, which has stimulated their use in anaerobic digestion modeling.

Modeling the activated sludge wastewater treatment plant plays an important role in improving its performance. However, there are many limitations of the available data for model identification, calibration, and verification, such as the presence of missing values and outliers. Because available data are generally short, these gaps and outliers in data cannot be discarded but must be replaced by more reasonable estimates. The aim of this study is to use the Kohonen self-organizing map (KSOM), unsupervised neural networks, to predict the missing values and replace outliers in time series data for an activated sludge wastewater treatment plant in Edinburgh, U.K. The method is simple, computationally efficient and highly accurate. The results demonstrated that the KSOM is an excellent tool for replacing outliers and missing values from a high-dimensional data set. A comparison of the KSOM with multiple regression analysis and back-propagation artificial neural networks showed that the KSOM is superior in per...

The aim of the study was to analyse the causes of the flooding problems being encountered in Lagos (Nigeria) and to recommend sustainable management solutions to them. Data on climate, drainage infrastructures and physical planning regulations were collected and extensively analysed. These were combined with evidence from field inspection and discussion with stakeholders, including relevant government departments, university researchers and selected residents. The investigation revealed that, contrary to popular wisdom, climate change or unusually high rainfall is not the primary cause of the flooding problems in Lagos. Rather, the increased urbanisation, lax planning laws in relation to the erection of buildings in flood plains and the lack or inadequacy of storm drainage facilities in the city are to blame. It is argued that a lasting solution to the flooding problem will require the incorporation of sustainable drainage systems within the existing flood management strategy for the city and planning for this must start now.