Cutting forces are small, and in many cases insignificant, compared with noise during the micro-machining of many non-metals. The Neural-Network-based Periodic Tool Inspector (NPTI) is introduced to evaluate tool condition periodically on a test piece during the machining of non-metal workpieces. The cutting forces are measured when a slot is being cut on the test piece and the neural network e...

The condition of joints in steel truss bridges is critical to railway operational safety. available methods for the quantitative assessment different types joint damage are, however, very limited. This paper numerically investigates feasibility using a probabilistic neural network (PNN) and finite element (FE) model updating technique assess bridges. A two-step identification procedure develope...

The purpose of this paper is to develop an intelligent diagnosis system for breast cancer classification. Artificial Neural Networks and Support Vector Machines were being developed to classify the benign and malignant of breast tumor in fine needle aspiration cytology. First the features were extracted from 92 FNAC image. Then these features were presented to several neural network architectur...

Received signal strength indicator (RSSI) based indoor localization technology has its irreplaceable advantages for many location-aware applications. It is becoming obvious that in the development of fifth-generation (5G) and future communication technology, will play a key role location-based application scenarios including smart home systems, manufacturing automation, health care, robotics. C...

Article history: Received July 20, 2011 Accepted 7 October 2011 Available online 8 October 2011 The purpose of this paper is to predict the S&P500 down moves with technical analysis indicators using learning vector quantization (LVQ) neural networks and probabilistic neural networks (PNN). In addition, entropy-based input selection technique is employed to improve the prediction accuracies. The...

Proteins are one of the most important parts of an organism because of their vital tasks. Consequently, it is necessary to know both the primary and secondary structure of a protein as closely related to its biological function. Artificial Neural Networks (ANNs) are a useful methodology for secondary structure prediction of proteins. In this study, a generalized regression neural network (GRNN)...

Phoneme recognition can be viewed as classifying multivariate observations. Multi-layer perceptrons (MLP) and probabilistic neural networks (PNN) approach the decision problem using two complementary models. The MLP models the discriminant surfaces between different phoneme categories, essentially by piece-wise planar approximations, while the PNN approximates class conditional probability dens...

False alarm and misdetected precipitation are prominent drawbacks of high-resolution satellite precipitation datasets, and they usually lead to serious uncertainty in hydrological and meteorological applications. In order to provide accurate rain area delineation for retrieving high-resolution precipitation datasets using satellite microwave observations, a probabilistic neural network (PNN)-ba...

In this work, the feasibility of flow pattern and oil hold up the prediction for vertical upward oil–water two–phase flow using pressure fluctuation signals was experimentally investigated. Water and diesel fuel were selected as immiscible liquids. Oil hold up was measured by Quick Closing Valve (QCV) technique, and five flow patterns were identified using high-speed photo...

In Australia, when stormwater systems were first introduced over 100 years ago, they were constructed independently of the sewer systems, and they are normally the responsibility of the third level of government, i.e., local government or city councils. Because of the increasing age of these stormwater systems and their worsening performance, there are serious concerns in a significant number o...