Forecast of Total Nitrogen in Wastewater Treatment Plants by means Techniques of Soft Computing
نویسنده
چکیده
Prediction in Wastewater Treatment Plants is an important purpose for decision-making. The complexity of the biological processes happening and, on the other hand, the uncertainty and incompleteness of the real data lead us to treat this problem modelling the data and via techniques of soft computing. Neural Networks has been the main procedure implemented. We have complemented it by genetic algorithms and fuzzy systems in order to select a suitable subset of variables. Statically results show that combining these methodologies we attaint reliable predictions of the Total Nitrogen which is one of the main variables for evaluating the water quality at the efluent of a Wastewater Treatment Plant. Key–Words: Environmental Modelling, Wastewater Treatment Plant, Total Nitrogen, Soft Computing, Neural Networks, Genetic Algoritms, Fuzzy Systems
منابع مشابه
Estimation of Phosphorus Reduction from Wastewater by Artificial Neural Network, Random Forest and M5P Model Tree Approaches
This study aims to examine the ability of free floating aquatic plants to remove phosphorus and to predict the reduction of phosphorus from rice mill wastewater using soft computing techniques. A mesocosm study was conducted at the mill premises under normal conditions, and reliable results were obtained. Four aquatic plants, namely water hyacinth, water lettuce, salvinia, and duckweed were use...
متن کاملEstimation of Phosphorus Reduction from Wastewater by Artificial Neural Network, Random Forest and M5P Model Tree Approaches
This study aims to examine the ability of free floating aquatic plants to remove phosphorus and to predict the reduction of phosphorus from rice mill wastewater using soft computing techniques. A mesocosm study was conducted at the mill premises under normal conditions, and reliable results were obtained. Four aquatic plants, namely water hyacinth, water lettuce, salvinia, and duckweed were use...
متن کاملUtilization of Soft Computing for Evaluating the Performance of Stone Sawing Machines, Iranian Quarries
The escalating construction industry has led to a drastic increase in the dimension stone demand in the construction, mining and industry sectors. Assessment and investigation of mining projects and stone processing plants such as sawing machines is necessary to manage and respond to the sawing performance; hence, the soft computing techniques were considered as a challenging task due to stocha...
متن کاملNeural Networks complemented with Genetic Algorithms and Fuzzy Systems for Predicting Nitrogenous Effluent Variables in Wastewater Treatment Plants
This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical or...
متن کاملApplication of non-linear regression and soft computing techniques for modeling process of pollutant adsorption from industrial wastewaters
The process of pollutant adsorption from industrial wastewaters is a multivariate problem. This process is affected by many factors including the contact time (T), pH, adsorbent weight (m), and solution concentration (ppm). The main target of this work is to model and evaluate the process of pollutant adsorption from industrial wastewaters using the non-linear multivariate regression and intell...
متن کامل