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In order to predict the price of candidates in acquisition and evaluate its feasibility, this paper puts forward a model of price prediction of candidates based on support vector machine. The model is trained by the data of market deals which were made in the past. The result of simulation and test indicates that average error of prediction is percent 7.71. It also proves that SVM has better performance...
This paper presents a new diagnosis method for classifying current waveform events that are related to a variety of induction machine faults. The method is composed of two sequential processes: feature extraction and classification. The essence of the feature extraction is to project a faulty machine signal onto a low dimension time-frequency representation (TFR), which is deliberately designed for...
This paper proposes a hybrid intelligent system for temperature forecasting in smart grids. In recent years, the uncertainties increase due to the competitive power markets and the emergence of renewable energy such as PV and wind power generation. The prediction of one-step ahead daily maximum temperature plays a key role to deal with Demand Response (DR) and PV under smart grid environment as well...
Neural networks are a useful alternative to Gaussian mixture models for acoustic modeling; however, training multilayer networks involves a difficult, nonconvex optimization that requires some “art” to make work well in practice. In this paper we investigate the use of arccosine kernels for speech recognition, using these kernels in a hybrid support vector machine/hidden Markov model recognition system...
Soft sensing technology is one of the topics of general interest in study on current process control, which has recently drawn considerable attention worldwide, and has stimulated researchers and engineers to make greater effort to reduce the cost/benefit-ratio for development and manufacture of bio-industrial processes both economically and environmentally. This paper introduced a kind of soft-sensor...
Noise source identification is essential for making noise reduction strategies. This paper presents an approach to acoustic noise identification by introducing modern spectrum estimation, Grey Support Vector Regression (GSVR). Modern spectrum was used to recognize the main noise source and GSVR was used to do curve fitting to recognize the similarity among different curves of power spectrum which...
The function approximation problem is to find the appropriate relationship between a dependent and independent variable(s). Function approximation algorithms generally require sufficient samples to approximate a function. Insufficient samples may cause any approximation algorithm to result in unsatisfactory predictions. To solve this problem, a function approximation algorithm called Weighted Kernel...
In order to improve the generalization performance of support vector machine (SVM), a support vector machine ensembling method based on independent component analysis (ICA) and fuzzy kernel clustering (FKC) was proposed. The ICA emphasizes the independence between the data characteristics and can effectively obtain a series of independent features, the performance of single SVM can be improved when...
Annually, the Philippine government'sDepartment of Public Works and Highways (DPWH) gathers visual road condition data for use in the rehabilitation of the Philippine national road network. Alongside the condition data of the road, inventory and traffic data are also gathered simultaneously. In literature, Visual Condition Index (VCI) is used to determine the condition of a road. The data gathering...
Strong correlation exists between river discharge and suspended sediment load. The relationship was used to estimate suspended sediment load by using linear regression model, power regression model, artificial neural network and support vector machine in this study. Records of river discharges and suspended sediment loads in Kaoping river basin were investigated as case study. Eighty-five percent...
The cost of experimental setup during an assembly process development of a chipset, particularly the under-fill process, can often result in insufficient data samples. In INTEL Malaysia, for example, the historical chipset data from an under fill process consists of only a few samples. As a result, existing machine learning algorithms for predictive modeling cannot be applied to this setting. Despite...
In the analysis of power system with respect to the load forecast, the currently used methods appeared to be insufficient. Based on this, the wavelet analysis (WA) combined with the fuzzy support vector kernel regression method was proposed by considering the characteristics of the load power in load forecast. To start with, wavelet transform was employed to acquire the wavelet decomposition of power...
Biometric authentication based on iris patterns is used for personal identification. Important attributes to identity applications include accuracy, speed and template size. Iris patterns are segmented by considering the maximum area of the connected components in the binary images. The iris region is decomposed into subregions. Hu moments are applied to the minimum variance subregions (MVS). The...
Support vector machines (SVMs) proved to be highly efficient in various classification tasks. However, the knowledge learned by the SVM is encoded in a long list of parameter values and it is not easy to comprehend what the SVM is actually computing. We show that certain types of SVMs are mathematically equivalent to a specific fuzzy — rule base, the fuzzy all — permutations rule base (FARB). This...
Automatic gender detection through facial features has become a critical component in the new domain of computer human observation and computer human interaction (HCI). Automatic gender detection has numerous applications in the area of recommender systems, focused advertising, security and surveillance. Detection of gender by using the facial features is done by many methods such as Gabor wavelets,...
LPR (License Plate Recognition) is a foundation component of modern transportation management systems. It uses a set of computer image-processing technologies to identify vehicle by its license plate. Character recognition is the core of LPR, which is essentially a multi-classification problem. The challenge is how to recognize every character of the license plate accurately and rapidly in case of...
This paper aims to develop intelligent Predictive Monitoring Emission Systems (PEMS) for three distinct case studies involving traffic, gasoline fuel tanks and large combustion plants (LCP). The underlying theme of pollutant emissions exists in all three case studies whereby the gases that are monitored are NO2, unburned hydrocarbons, and SO2. These pollutants can cause grievous harm to health, environment...
On the basis of analyzing disadvantages of conventional prediction model of air-and-screen cleaning device, a new regression model based on support vector machine was proposed to predict and control of cleaning process precisely. Parameters of ε-SVR models were determined utilizing non-heuristic Grid Search, heuristic GA and PSO which could avoid the choice of randomness. The effect of samples in...
The price of crude oil is tied to major economic activities in all nations of the world, as a change in the price of crude oil invariably affects the cost of other goods and services. This has made the prediction of crude oil price a top priority for researchers and scientists alike. In this paper we present an intelligent system that predicts the price of crude oil. This system is based on Support...
Under real and continuously improving manufacturing conditions, lithography hotspot detection faces several key challenges. First, real hotspots become less but harder to fix at post-layout stages; second, false alarm rate must be kept low to avoid excessive and expensive post-processing hotspot removal; third, full chip physical verification and optimization require fast turn-around time. To address...
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