In this paper, two CI techniques, namely, single multiplicative neuron (SMN) model and adaptive neuro-fuzzy inference system (ANFIS), have been proposed for time series prediction. A variation of particle swarm optimization (PSO) with co-operative sub-swarms, called COPSO, has been used for estimation of SMN model parameters leading to COPSO-SMN. The prediction effectiveness of COPSOSMN and ANF...

this study investigates the prediction model of compressive strength of self–compacting concrete (scc) by utilizing soft computing techniques. the techniques consist of adaptive neuro–based fuzzy inference system (anfis), artificial neural network (ann) and the hybrid of particle swarm optimization with passive congregation (psopc) and anfis called psopc–anfis. their performances are comparativ...

The subject of this work is to propose a new method based on the ANFIS system and PSO algorithm conceive model for estimating solubility solid drugs in supercritical CO2 (sc-CO2). high nonlinear process was modeled by neuro-fuzzy approach (NFS). used two purposes: replacing standard backpropagation training NFS optimizing process. validation strategy has been carried out using linear regression...

In this paper, two CI techniques, namely, single multiplicative neuron (SMN) model and adaptive neurofuzzy inference system (ANFIS), have been proposed for time series prediction. A variation of particle swarm optimization (PSO) with co-operative sub-swarms, called COPSO, has been used for estimation of SMN model parameters leading to COPSO-SMN. The prediction effectiveness of COPSO-SMN and ANF...

Accurate solar radiation (SR) prediction is one of the essential prerequisites harvesting energy. The current study proposed a novel intelligence model through hybridization Adaptive Neuro-Fuzzy Inference System (ANFIS) with two metaheuristic optimization algorithms, Salp Swarm Algorithm (SSA) and Grasshopper Optimization (GOA) (ANFIS-muSG) for global SR at different locations North Dakota, USA...

To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extr...

Predicting groundwater levels is critical for ensuring sustainable use of an aquifer’s limited reserves and developing a useful abstraction management strategy. The purpose this study was to assess the predictive accuracy estimation capability various models based on Adaptive Neuro Fuzzy Inference System (ANFIS). These included Differential Evolution-ANFIS (DE-ANFIS), Particle Swarm Optimizatio...

The development and constant improvement of accurate predictive models electricity generation from photovoltaic systems provide valuable planning tools for designers, producers, self-consumers. In this research, an adaptive neuro-fuzzy inference model (ANFIS) was developed, which is intelligent hybrid that integrates the ability to learn by itself provided neural networks function language expr...

clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...