Enlightened by the properties of scale-free network model, BA model is extended and introduced into particle swarm optimization, and a novel two-phase particle swarm optimization with scale-free network model (TPSO-SN...
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Enlightened by the properties of scale-free network model, BA model is extended and introduced into particle swarm optimization, and a novel two-phase particle swarm optimization with scale-free network model (TPSO-SNM) is proposed. At the early stages of the algorithm, particles are randomly distributed in a ring, new particles are continuously added into the structure based on the node degree and the distance between nodes. At the same time, the global optimum in evolution equation is substituted with the average optimal location in neighborhood. Simulation results show that the new method has better ability to find the global optimum solution.
This paper describes our research on learning browsing behavior model for predicting the current information need of a web user. This inference is based on a parameterized model of how the sequence of browsing behavio...
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This paper describes our research on learning browsing behavior model for predicting the current information need of a web user. This inference is based on a parameterized model of how the sequence of browsing behavior indicates the degree to which page content satisfies the user's information need, and the model parameters can be estimated using standard methods from a labelled corpus. Data from lab experiments demonstrate that the prediction model can effectively identify the information needs of new users, browsing previously unseen pages. The paper concludes with an overview of our WebIC which integrates the model into a web browser, to help the user find the relevant information effectively from the web.
Decision rules mining is an important issue in machine learning and data ***,most proposed algorithms mine categorical data at single level,and these rules are not easily understandable and really useful for ***,a new...
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Decision rules mining is an important issue in machine learning and data ***,most proposed algorithms mine categorical data at single level,and these rules are not easily understandable and really useful for ***,a new approach to hierarchical decision rules mining is provided in this paper,in which similarity direction measure is introduced to deal with hybrid *** approach can mine hierarchical decision rules by adjusting similarity measure parameters and the level of concept hierarchy trees.
Some potential research hotspot problems on swarm intelligence in the “Three-River Headwaters” region are surveyed form an artificial intelligence perspective. The scientific analysis and demonstration results in th...
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Some potential research hotspot problems on swarm intelligence in the “Three-River Headwaters” region are surveyed form an artificial intelligence perspective. The scientific analysis and demonstration results in this paper confirm that the scheme that application of advanced artificial intelligent technology and the idea of circular economy in the regional economic development of the “Three-River Headwaters” region so as to make the rich resources can be effective utilization and realize the sustainable development which is feasible and accord with the requirement of the scientific development view.
In this paper we consider passive airborne receivers that use backscattered signals from sources of opportunity transmitting fixed-frequency waveforms. Due to its combined passive synthetic aperture and the fixed-freq...
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ISBN:
(纸本)9781424458110
In this paper we consider passive airborne receivers that use backscattered signals from sources of opportunity transmitting fixed-frequency waveforms. Due to its combined passive synthetic aperture and the fixed-frequency nature of the transmitted waveforms, we refer to the system under consideration as Doppler Synthetic Aperture Hitchhiker (DSAH). We present a novel image formation method for DSAH. Our method first correlates the windowed signal obtained from one receiver with the windowed, filtered, scaled and translated version of the received signal from another receiver. This processing removes the transmitter related variables from the phase of the Fourier integral operator that maps the radiance of the scene to the correlated signal. We next use the microlocal analysis to reconstruct the scene radiance by the weighted-backprojection of the correlated signal. This imaging algorithm can put the visible edges of the scene radiance at the correct location, and under appropriate conditions, with correct strength. Additionally, it is an analytic reconstruction technique which can be made computationally efficient. We show that the resolution of the image is directly related to the length of the support of the windowing function and the frequency of the transmitted waveform. The image reconstruction method is applicable with both cooperative and non-cooperative sources of opportunity using one or more airborne receivers. We present numerical simulations to demonstrate the performance of the image reconstruction method and to verify the theoretical results.
A consensus feature-ranking approach has been applied to the study of localization-related temporal lobe epilepsy (TLE) in order to evaluate the relative discriminative power of individual attributes. Cases were selec...
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A consensus feature-ranking approach has been applied to the study of localization-related temporal lobe epilepsy (TLE) in order to evaluate the relative discriminative power of individual attributes. Cases were selected on the basis of a postoperative outcome free of disabling seizures (i.e., Engel class I) in order to establish a definitive laterality of focal epileptogenicity. Several quantitative measures made available by imaging and electrographic studies are considered and the most discriminative of these are quantitatively prioritized for the lateralization of focal epileptogenicity. Cases requiring extraoperative electrocorticography were examined as a subgroup to establish whether the current method of analysis could distinguish laterality sufficiently well to avoid the requirement for intracranial electrode implantation.
Development of a feature ranking method based upon the discriminative power of features and unbiased towards classifiers is of interest. We have studied a consensus feature ranking method, based on multiple classifier...
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Development of a feature ranking method based upon the discriminative power of features and unbiased towards classifiers is of interest. We have studied a consensus feature ranking method, based on multiple classifiers, and have shown its superiority to well known statistical ranking methods. In a target environment such as a medical dataset, missing values and an unbalanced distribution of data must be taken into consideration in the ranking and evaluation phases in order to legitimately apply a feature ranking method. In a comparison study, a Performance Index (PI) is proposed that takes into account both the number of features and the number of samples involved in the classification.
The gramian approximation methods have been proposed recently to overcome the high computing costs of classical balanced truncation based reduction methods. But those methods typically gain efficiency by projecting th...
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ISBN:
(纸本)9781605588377
The gramian approximation methods have been proposed recently to overcome the high computing costs of classical balanced truncation based reduction methods. But those methods typically gain efficiency by projecting the original system only onto one dominant subspace of the approximate system gramian (for instance using only controllability gramian). This single gramian reduction method can lead to large errors as the subspaces of controllability and observability can be quite different for general interconnects with unsymmetric system matrices. In this paper, we propose a fast balanced truncation method where the system is balanced in terms of two approximate gramians as achieved in the classical balanced truncation method. The novelty of the new method is that we can keep the similar computing costs of the single gramian method. The proposed algorithm is based on a generalized SVD-based balancing scheme such that the dominant subspace of the approximate gramian product can be obtained in a very efficient way without explicitly forming the gramians. Experimental results on a number of published benchmarks show that the proposed method is much more accurate than the single gramian method with similar computing costs.
This paper proposes a method of 3D topological reconstruction for informationally structured space including sensor networks and robot partners for co-existing with people. The informationally structured space realize...
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This paper proposes a method of 3D topological reconstruction for informationally structured space including sensor networks and robot partners for co-existing with people. The informationally structured space realizes the quick update and access of valuable and useful information for both people and robots on real and virtual environments. In this paper, we use distance information and color information measured by 3D distance image sensor and CMOS camera for 3D topological reconstruction. First, we propose an extraction method of objects from the background image based on Hough transform as preprocessing. Next, we propose a method of 3D topological reconstruction based on growing neural gas to construct informationally structured space. Finally, we show experimental results of the proposed method and discuss the effectiveness of the proposed method.
The accuracy and efficiency of cost estimation methodology for web-based application is very important for software development as it would be able to assist the management team to estimate the cost. Furthermore, it w...
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The accuracy and efficiency of cost estimation methodology for web-based application is very important for software development as it would be able to assist the management team to estimate the cost. Furthermore, it will ensure that the development of cost is within the planned budget and provides a fundamental motivation towards the development of web-based application project. The literature review reveals that COCOMO II provides accurate result because more variables are considered including reuse parameter. The parameter is one of the essential variables in estimating the cost in web-based application development. This research investigates the feasibility to combine and implement COCOMO II and expert judgment technique in a tool called WebCost. In estimating a cost, the tool considers all variables in COCOMO II and requires expert judgment to key-in the input of the variables such as project size, project type, cost adjustment factor and cost driven factor. Developed in JAVA, WebCost is proven able to estimate cost and generate its estimation result. The usability evaluation conducted had shown that WebCost is usable when compared with other tools, it has its own advantages. WebCost is evidence suitable for everyone especially the project managers, software practitioners or software engineering student in handling the cost estimation tasks.
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