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In Machine Learning applications, the selection of the classification algorithm depends on the problem at hand. This paper provides a comparison of the performance of the Support Vector Machine (SVM) and the Artificial Neural Network (ANN) for food intake detection. A combination of time domain (TD) and frequency domain (FD) features, extracted from signals captured using a jaw motion sensor, were...
To improve the prediction accuracy of crude oil price even in current complicated international situation, this paper proposed a novel model linking firefly algorithm (FA) with least squares support vector regression (LSSVR), namely FA-LSSVR. In this hybrid intelligent model, FA is used to find the optimal values of LSSVR parameters (i.e., penalty coefficient and kernel function parameters), in order...
Neural network (NN) modelling approach is often used for non-linear system identification. Building a NN for some identification problem starts by choosing its structure and initial weights. There is no exact method to determine the optimal initialisation for a NN, but some authors have used support vector regression (SVR) to initialise a RBFNN which could be considered as a systematic way. This paper...
One of the key feature of modern architectures is deep memory hierarchies. In order to exploit this feature, one has to expose data locality with-in a program. Loop tiling is an optimization phase in modern compilers which is used to transform a loop for exposing data locality. Selecting the best tile size for a given architecture and compiler is known as Optimal Tile Size Selection Problem. It is...
This paper presents an approach combining machine learning (ML), cross-validation methods and cellular automata (CA) model for simulating land use changes in Luxembourg and the areas adjacent to its borders. Throughout this article, we emphasize the interest in using ML methods as a base of CA model transition rule. The proposed approach shows promising results for prediction of land use changes over...
Many intelligent transportation systems (ITS) applications require accurate prediction of traffic parameters. Previous studies have shown that data driven machine learning methods like support vector regression (SVR) can effectively and accurately perform this task. However, these studies focus on highways, or a few road segments. We propose a robust and scalable method using n-SVR to tackle the problem...
Automatic speech recognition analysis has been an active part in computer science for more than two decades. In general, to detect an emotion, long continuous signal is needed. Relative amplitude reduces bias of glottal mutation of speech wave amplitude and obtains a normalized measure without concern of information from being distinct in feature. Nonverbal communication plays crucial role in human-human...
Industry is moving towards many-core processors, which are expected to consist of tens or even hundreds of cores. One of these future processors is the 48-core experimental processor Single-Chip Cloud Computer (SCC). The SCC was created by Intel Labs as a platform for many-core research. The characteristics of this system turns it into a big challenge for researchers in order to extract performance...
Signature (Latin - signare) is a handwritten stylized form of identification of its owner. Often handwritten signatures are generally used in secured identity preservation. An ideal signature recognition system handles image noise as well as that of learning unique patterns in an individual's signature. This paper analyzes the performance of artificial neural network (ANN) architectures and Gaussian...
When trying to solve classification or time-series prediction problem statements by the application of Artificial Neural Networks (ANNs), commonly applied structures like feed forward or recurrent Multi-Layer Perceptrons (MLP) characteristically tend to come up with bad performance and accuracy. This is especially the case when dealing with manifold datasets containing numerous input (predictors)...
A classification system that accurately categorizes caller behavior within Interactive Voice Response systems would assist in developing good automated self service applications. This paper details the implementation of such a classification system for a pay beneficiary application. Adaptive Neuro-Fuzzy Inference System (ANFIS), Feed forward Artificial Neural Network (ANN) and Support Vector Machine...
A considerable amount of research has been conducted on gender and age estimation from facial images over the last few years, and state-of-the-art technology has accomplished a practical accuracy level for a homogeneous race such as Japanese or Korean. However, achieving the same accuracy level across multiple races such as Caucasian, African American, and Hispanic is still highly challenging because...
Coherency Sensitive Hashing (CSH) extends Locality Sensitivity Hashing (LSH) and PatchMatch to quickly find matching patches between two images. LSH relies on hashing, which maps similar patches to the same bin, in order to find matching patches. PatchMatch, on the other hand, relies on the observation that images are coherent, to propagate good matches to their neighbors, in the image plane. It uses...
As a typical and special complexity gigantic system, the power system is facing the challenge from complexity science in the aspects of load forecasting and its management. Therefore, on the basis of complex system theory, a new method used for predicting the short-term load is proposed by means of a series of subsystems divided according to the different areas and types of regional electricity. Support...
The support vector machine(SVM) based on structural risk minimization is more and more widely used to solve the problems of small sample, nonlinear, high dimensional and local minimization attributes because of its good generalization. But the performance of SVM is influenced by the model parameters very much. At present there is not a unified method of model selection, which makes it troublesome...
Using both qualitative and quantitative analysis, a set of relatively integrated evaluation indexes was developed to analyze the urban planning process in Guanzhong urban agglomeration. Key impact factors of coordinated development obtained from literature analysis were used as input, and the degree of coordinated development during 1988~2008 calculated by principal component analysis and the coordinated...
The prediction strength of cement is an important task in civil engineering. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the 28d strength of cement. The seven input variables used for the SVM model for prediction of strength are content of slag, SO3 content, cement fineness, 1d compressive strength and folding...
Forecast combination, which is a method to combine the result of several predictors, offers a way to improve the forecast result. Several methods have been proposed to combine the forecasting results into single forecast, namely the simple averaging, weighted average on validation performance, or non-parametric combination schemas. Recent literature uses dimensional reduction method for individual...
Support vector machine (SVM) has been widely used for its outstanding performance. But, it still has flaws. One of them is that SVM is unit sensitive. In this paper, we analyze how will the different units effect the SVM. Then, we propose a preprocess method not only to conquer this flaw, but also improve the generalization precision of SVM. The preprocess method is base on decision tree(DT). The...
Sea target detection is an important goal for military purposes and navigation. Environmental noise and sea clutter are two major problems in sea target detection. A new novel Neural Network in Kernel Space (NNKS) is presented for classification of the target and non-target in color images, and it is followed with a new kernel neuron sea target detection system (KNNS) which is efficient especially...
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