To cope up with the strict emission and product quality standards the process industries are stern for the maintenance of the product quality and waste emission. For process industries, online hardware analyzers are costly alternate for analyzing the product quality, they are switching to online soft sensors which are cheap and efficient in use. In this work, soft sensor based on artificial neu...

in this paper, an adaptive neuro fuzzy inference system (anfis) based control is proposed for the tracking of a micro-electro mechanical systems (mems) gyroscope sensor. the anfis is used to train parameters of the controller for tracking a desired trajectory. numerical simulations for a mems gyroscope are looked into to check the effectiveness of the anfis control scheme. it proves that the sy...

The methods of ordinary least-squares regression (OLSR), fuzzy regression (FR), and adaptive network fuzzy inference system (ANFIS) are compared in inferring operating rules for a reservoir operations problem. Dynamic programming (DP) is used to provide the input-output data set to be used by OLSR, FR, and ANFIS models. The coefficients of an FR model are found by solving a linear programming (...

In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycl...

A novel data-driven soft sensor is designed for online product quality prediction and control performance modification in industrial units. A combined approach of time variable parameter (TVP) model, dynamic auto regressive exogenous variable (DARX) algorithm, nonlinear correlation analysis and criterion-based elimination method is introduced in this work. The soft sensor performance validation...

Forecasting the bank profile shape of stable hydraulic channels using empirical, experimental and numerical models is special consideration among fluid mechanic river science engineers. In present paper, application soft computing methods evaluated in predicting geometry channel cross sections. this way, a combination Particle Swarm Optimization (PSO) algorithm with an Adaptive Neuro-Fuzzy Infe...

The ANFIS is the product of two methods, neural networks, and fuzzy systems. If both these intelligent methods are combined, better reasoning will be obtained in term of quality and quantity. In other words, both fuzzy reasoning and neural network calculation will be available simultaneously [7]. This ANFIS technique has been successfully applied by many researchers for sensor-based autonomous ...

Soft-sensors for estimating in real-time important quality variables are a key technology in modern process industry. The successful development of a soft-sensor whose performance does not deteriorate with time and changing process characteristics is troublesome and only seldom achieved in real-world setups. The design of soft-sensors based on local regression models is becoming popular. Simpli...

−The Joint Probabilistic Data Association (JPDA) solves single sensor multi-target tracking in clutter, but it cannot be used directly in multi-sensor multi-target tracking (MMT) and has high computational complexity with the number of targets and the number of returns. This paper presents a hybrid method to implement MMT by combing Maximum Likelihood Estimation (MLE) with Adaptive Neuro-Fuzzy ...