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The precision of ideal site index curve model mainly depends on the solved parameters of the fitting equation. To archive high precision of model, a particle swarm optimization algorithm with iterative improvement strategy was proposed to solve parameters of the model. The improved algorithm makes each particle update it's current velocity and position dimension by dimension. The result shows the...
A detailed description of tone and intonation is beneficial for many spoken language processing applications. In traditional methods for tone and pitch accent modeling, prosodic features, such as pitch, energy and duration, have been used. Here, a novel system that uses auditory attention cues is proposed for tone and fine grained pitch accent classification. The auditory attention cues are biologically...
Rule ranking is a crucial step in Associative Classification (AC), AC algorithms proposed many ranking methods which aim to improve the accuracy of the classifier. In this paper we propose a new model in rule ranking, namely Hybrid-RuleRank, which employs a hybrid Artificial Intelligence (AI) technique that combines Simulated Annealing (SA) with Genetic Algorithm (GA), the new model tested against...
In remote sensing image classification, it is commonly assumed that the distribution of the classes is stable over the entire image. This way, training pixels labeled by photointerpretation are assumed to be representative of the whole image. However, differences in distribution of the classes throughout the image make this assumption weak and a model built on a single area may be suboptimal when...
Attracting more students into science and engineering disciplines concerned many researchers for decades. Literature used traditional statistical methods and qualitative techniques to identify factors that affect student retention up most and predict their persistence. In this paper we developed two neural network models using a feed-forward backpropagation network to predict retention for students...
The influence of climate change on water consumption under changing economic background has always been kept a important issue by global research institute. Taking Dongguan city as a study object, the influence factors of water requirement are divided into climate factor economic factor and social factor. Water demand forecasting models are established on different influence factors to analyze the...
For the huge-investment project like rail transit in city, the forecast passenger demand is very important to its planning and feasibility studying. Traditional forecasting methods or models can not fully use all the survey data in passenger demand forecast, and some information is wasted. They have another deficiency that receives a low accuracy value in demand forecasting for incomplete factors...
This paper analyzes the 21 original geometric errors of machine tools and the resulting coupling effects, namely geometric composite errors, and then arrives at the conclusion that the key point of error compensation for CNC machine tools is error value, a function of command position. And it also points the errors can be decoupled into error components of each axis-direction. Therefore, according...
Low-carbon, the only way to the sustainable development of all countries around the world, has become a hot topic. Carbon flux (FC) is closely related to many factors in ecological environment as an index of global carbon emissions. Therefore, it is very important to find effective methods to study the relationship between FC and environmental factors. A predicted model based on wavelet networks is...
In this paper, we report on an experiment conducted to test the effects of different hand representations on near space pointing performance and user preference. Subjects were presented with varying levels of hand realism, including real hand video, a high and a low level 3D hand model and an ordinary 3D pointer arrow. Behavioural data revealed that an abstract hand substitute like a 3D pointer arrow...
This paper proposed the heart disease diagnosis system using nonlinear ARX (NARX) model. The system uses neural network for model estimation and classification of Normal and several heart diseases based on heart sounds. In classification, a spectrogram was applied to the modeled heart sounds for features extraction and selection. The features were fed to the FFNN and trained using Resilient Backpropagation...
In this paper, we present a novel methodology for computing statistical shape models (SSM's) by leveraging the medial axis model to determine shape variations between objects. Landmark based SSM's (LSSM's) are a popular approach to describing valid shape variation in an object of interest by applying principal component analysis to a set of landmarks on the surface of the object. However, defining...
In order to create valid CAD (computer-aided design) model for planning orthopedic operations, rapid prototyping, designing of implants, etc., the accurate definition of geometry and topology of all regions of human tibia is essential. Therefore it is logical to base process of geometrical modeling of human tibia on its anatomical and morphological properties. This paper presents and compares the...
Wireless Sensor Network for their rapid deployment can be used in habitat monitoring for detecting fire and in disaster for helping rescue teams. Node localization is key factor for some applications. We propose the Triangular Centroid Localization algorithm (TCL). It is based in simple trigonometric figures and it does not require special hardware or synchronization time. In our simulations using...
Statistics plays an important role in many areas especially in classification tasks. Logistic Regression Model is one popular technique to solve problems, in particular, medical problems. P-Thalassemia, a common genetic disorder, lends itself to is interesting for using MLR to classify types of P-Thalassemia. There are several types of Thalassemia in the world, especially Thailand. From many methods...
Rapidly and accurately estimating the impact of design decisions on performance metrics is critical to both the manual and automated design of wireless sensor networks. Estimating system-level performance metrics such as lifetime, data loss rate, and network connectivity is particularly challenging because they depend on many factors, including network design and structure, hardware characteristics,...
Recently, an increasing number of online news websites have come to provide news browsing and retrieval services. For certain topics, certain news websites may hold sentiment bias, and therefore select and edit information according to their own standpoints before delivering news articles. Lacking conscious awareness of websites' sentiment bias may result in blind obedience to the reported information...
The importance to financial institutions of accurately evaluating the credit risk posed by their loan granting decisions cannot be underestimated; it is underscored by recent credit assessment failures that contributed greatly to the so-called "great recession" of the late 2000s. The paper compares the classification accuracy rates of several traditional and computational intelligence methods...
It is important to monitor vegetation such as forests in order to understand the impacts of global climate change on terrestrial ecosystems and agriculture crops to ensure food security to the people and livestock. Remote sensing data such as polarimetric SAR data plays a useful role in estimating total vegetation cover and biomass. In this study, a radar vegetation index (RVI) were used to separate...
We have recently introduced new generative semi supervised mixtures with more fine-grained class label generation mechanisms than previous methods. Our models combine advantages of semi supervised mixtures, which achieve label extrapolation over a component, and nearest-neighbor (NN)/nearest-prototype (NP) classification, which achieves accurate classification in the vicinity of labeled samples. Our...
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