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Rapid, accurate and reliable measurements of biological oxygen demand (BOD) are a key basis for monitoring and controlling wastewater treatment processes (WWTP). A kind of soft measurement based on the dynamic neural network (DNN) is proposed in this paper, which can be used to monitor and model the important parameters of the wastewater treatment process on-line. The main parts of the soft measurement...
This paper introduces a virtual arthroscopy training simulator as a beneficial tool for partial meniscectomy procedure. The modeling methods of virtual environment, haptic interface establishment, and the system integration are described in detail. With the combination of interactive visual and haptic feedback, the simulator is designed to aid surgeons in getting acquainted with the arthroscopic view...
This paper proposes an interval type-2 recurrent fuzzy neural network (IT2RFNN) for dynamic system identification. The antecedent parts in each recurrent fuzzy rule in the IT2RFNN are interval type-2 fuzzy sets, and the consequent part is of the Takagi-Sugeno-Kang (TSK) type with interval weights. The recurrent structure in the T2RFNN enables it to handle dynamic system identification problems with...
The decision trees and their variants recently have been proposed. All trees used are fixed M-ary tree-structured, such that the training samples in each node must be artificially divided into a fixed number of branches. This study proposes a fuzzy variable-branch decision tree (FVBDT) based on the fuzzy genetic algorithm (FGA). The FGA automatically searches for the proper number of branches of each...
PID controllers are popular in industrial applications, as they are easy to install and reasonably robust. However, for highly nonlinear systems, the performance of PID controllers can deteriorate quite fast. It is necessary to develop nonlinear PID controllers for controlling nonlinear processes. An approach to design these controllers is to switch between several linear PID controllers using fuzzy...
This paper investigates the failure prediction problem for multivariable and multi-failure-mode complex systems based on performance degradation. In our treatment, neural network is employed to simulate system performance degradation and to predict the health states of functional modules. BP network and Learning Vector Quantization (LVQ) network are used simultaneously to simulate and to predict future...
A direct neural interface system (NIS) promises to provide communication and independence to persons with paralysis by harnessing intact motor cortical signals to enable controlling prosthetic devices. An intracortical NIS aims to achieve this by sensing extracellular neuronal signals through chronically implanted microelectrodes and by decoding the spiking activity of neurons into prosthetic control...
A nondestructive optical method for determining the geographic origins of rice was investigated. Average absorption spectra of rice for three different geographic origins were analyzed. Direct orthogonal signal correction (DOSC), standard normal variate transformation (SNV) combined with detrending, multiply scatter calibration (MSC) and Savitzky-Golay second-order derivative transformation (S.Golay...
The ever increasing demand and restriction on having additional new infrastructure, forces the existing power system network to work at its maximum possible limits. In order to increase the power transfer through given infrastructure, the use of FACTS devices is common and very well known. Here a model predictive control based TCSC controller is used for improving the transient stability response...
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