-In order to overcome the defects of the traditional static load modeling in coalmine, a new modeling method is proposed in this paper. First, a new clustering method based on improved PSO algorithm is presented to classify the load data in order to reduce the number of load model before modeling. Second, RBF neural network based on improved PSO algorithm is put forward to establish aggregate l...

This paper presents an optimum network structure based on a BBO tuned adaptive neuro-fuzzy inference system (ANFIS) to control active suspension (ASS). The unsupervised learning via Biogeography-Based Optimization (BBO) algorithm is used train the ANFIS network. optimal proportional-integral-derivative controller LQR method generate training data set. base Fuzzy c-means (FCM) clustering applied...

A MANET consists of a group mobile nodes. In MANET, scalability and mobility have greater influence on routing performance. The clustering technique plays vital role in enhancing the mechanism improving network lifetime large-scale like MANET. process will degrade performance if malicious node is chosen as Cluster Leader (CL). Thus, secure very challenging task. To overcome this problem, follow...

Parkinson’s disease (PD) is a progressive neurodegenerative disorder. Autism spectrum disorder (ASD) neurodevelopment Clinical decision-making process complex. Due to complex nature of sign and its symptoms clinical decision making may lead misclassification. To deal with such medical problems methods or approaches soft computing play an important role. This paper will focus on presenting integ...

This paper focuses on an analysis of demand response in a smart grid context, presenting the model considerations and architecture. Domestic consumption is divided into groups in order to cover the adequate modeling. A fuzzy subtractive clustering method is applied to demand response on several domestic consumption scenarios and results analyses are presented. The demand response developed mode...

introduction: a total dissolved solid (tds) is an important indicator for water quality assesment. since the composition of mineral salts and discharge affects the tds of water, it is important to understand the relationships of mineral salts composition with tds. materials and methods: in this study, methods of artificial neural networks with five different training algorithm,levenberg-marquar...

Pyrite oxidation, Acid Rock Drainage (ARD) generation, and associated release and transport of toxic metals are a major environmental concern for the mining industry. Estimation of the metal loading in ARD is a major task in developing an appropriate remediation strategy. In this study, an expert system, the Multi-Output Adaptive Neuro-Fuzzy Inference System (MANFIS), was used for estimation of...

In the present study, the adaptive neuro-fuzzy inference system (ANFIS) is developed for the prediction of effective thermal conductivity (ETC) of different fillers filled in polymer matrixes. The ANFIS uses a hybrid learning algorithm. The ANFIS is a class of adaptive networks that is functionally equivalent to fuzzy inference systems (FIS). The ANFIS is based on neuro-fuzzy model, trained wit...

Prediction of student’s performance is potentially important for educational institutions to assist the students in improving their academic performance, and deliver high quality education. Developing an accurate student’s performance prediction model is challenging task. This paper employs the Adaptive NeuroFuzzy Inference system (ANFIS) for student academic performance prediction to help stud...

A primary application of web usage profiling is in model-based collaborative filtering (CF) for building recommender systems used for web personalization. CF techniques used for recommendation require accumulation of vast amount of historical user-preference information, which is queried to provide a personalized experience. Model-based CF techniques are preferred over the somewhat more accurat...