The present work proposes a new approach in modelling the biological wastewater treatment plant: The anaerobic digestion by multiple models. Although a mathematical model already exists, but the interaction between the various variables is strongly not linear and is modelled in the form of rather complex algébro-differential equations. So, by using the method of subtractive clustering, the mult...

Objective: Soil temperature serves as a key variable in hydrological investigations to determine soil moisture content as well as hydrological balance in watersheds. The ingoing research aims to shed lights on potential of artificial neural networks (ANNs) and Neuro-Fuzzy inference system (ANFIS) to simulate soil temperature at 5-100 cm depths. To satisfy this end, climatic and...

The SIFT descriptor is one of the most widely used descriptors and Is very stable in regard to change in rotation, scale, affine, illumination, etc. However, because of the greater emphasis on its insensitivity to geometric changes, this descriptor is weak in various illuminations. This method is based on key points extracted from the image. If there are many such points, a lot of time will be ...

A new method for spike sorting is proposed which partly solves the overlapping problem. Principal component analysis and subtractive clustering techniques are used to estimate the number of neurons contributing to multi-unit recording. Spike templates (i.e. waveforms) are reconstructed according to the clustering results. A template-matching procedure is then performed. Firstly all temporally d...

association rules are among important techniques in data mining which are used for extracting hidden patterns and knowledge in large volumes of data. association rules help individuals and organizations take strategic decisions and improve their business processes. extracted association rules from a database contain important and confidential information that if published, the privacy of indivi...

This series of studies represents an effort to extend the subtractive method of Bonders to the analysis of depth of processing in simple classification tasks. The stimuli are always pairs of items (letters, nonsense forms, digits) to which S must respond "same" or "different" as quickly as possible. Levels of instruction are physical identity (e.g., AA), name identity (e.g., Aa), and rule ident...

Determining the rules that lead to expansion of urban areas has always been a challenging factor in modeling. To overcome this issue, an ANFIS model is proposed enhance simulation growth through automatic production transition rules. Hence, 22 models were trained using different division methods and Cellular Automata-based Markov Chain (CA-MC) was developed examine their efficiencies. The resul...

In current study, a particle swarm clustering method is suggested for clustering triangular fuzzy data. This clustering method can find fuzzy cluster centers in the proposed method, where fuzzy cluster centers contain more points from the corresponding cluster, the higher clustering accuracy. Also, triangular fuzzy numbers are utilized to demonstrate uncertain data. To compare triangular fuzzy ...