86 Result(s)
within
Computer Science
Data Mining and Knowledge Discovery
Probability and Statistics in Computer Science
**li Meng
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Chapter and Conference Paper
A Biological Text Retrieval System Based on Background Knowledge and User Feedback
Efficiently finding the most relevant publications in large corpus is an important research topic in information retrieval. The number of biological literatures grows exponentially in various publication datab...
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Chapter and Conference Paper
Resource Allocation and Scheduling Problem Based on Genetic Algorithm and Ant Colony Optimization
Faced with the increasing growth of container throughput and more large ships in shorter time, a key factor of success is to generate the best resource allocation plan for the future. This paper discusses a he...
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Chapter and Conference Paper
A Parallel Algorithm for Finding Related Pages in the Web by Using Segmented Link Structures
In this paper, a simple but powerful algorithm: block co-citation algorithm is proposed to automatically find related pages for a given web page, by using HTML segmentation technologies and parallel hyperlink ...
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Article
Combining support vector regression with feature selection for multivariate calibration
Multivariate calibration is a classic problem in the analytical chemistry field and frequently solved by partial least squares (PLS) and artificial neural networks (ANNs) in the previous works. The spaciality...
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Article
Extraction of microsaccade-related signal from single-trial local field potential by ICA with reference
During visual fixation, we unconsciously make tiny, involuntary eye movements or ‘microsaccades’, which have been shown to have a crucial influence on analysis and perception of our visual environment. Given t...
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Article
Qualitative analysis and application of locally coupled neural oscillator network
This paper investigates a locally coupled neural oscillator autonomous system qualitatively. By applying an approximation method, we give a set of parameter values with which an asymptotically stable limit cyc...
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Chapter and Conference Paper
Knowledge Transfer for Multi-labeler Active Learning
In this paper, we address multi-labeler active learning, where data labels can be acquired from multiple labelers with various levels of expertise. Because obtaining labels for data instances can be very costl...
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Article
Extreme learning machine terrain-based navigation for unmanned aerial vehicles
Unmanned aerial vehicles (UAVs) rely on global positioning system (GPS) information to ascertain its position for navigation during mission execution. In the absence of GPS information, the capability of a UAV...
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Article
Extreme learning machine-based predictor for real-time frequency stability assessment of electric power systems
As a novel and promising learning technology, extreme learning machine (ELM) is featured by its much faster training speed and better generalization performance over traditional learning techniques. ELM has fo...
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Article
Multi-robot task allocation using CNP combines with neural network
Contract Net Protocol is a suitable method for multi-robot task allocation problems. However, it is difficult to find a function to evaluate robots’ bids when each robot gives more than one bid price to reflec...
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Article
Robots learn to dance through interaction with humans
In this paper, we investigated an approach for robots to learn to adapt dance actions to human’s preferences through interaction and feedback. Human’s preferences were extracted by analysing the common action ...
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Article
Evolutionary dynamics of sales agents’ promotional effort on small-world networks
In reality, manufacturers motivate sales agents to increase promotional effort with the sales rebate and penalty contract, the agents always concern about the fairness, and information flow structure among ag...
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Article
A forecasting method of forest pests based on the rough set and PSO-BP neural network
In order to improve the forecasting accuracy of the occurrence period of insect pests, this paper proposes a kind of forecasting method based on the combination of rough set theory and improved PSO-BP neural n...
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Article
A density-adaptive affinity propagation clustering algorithm based on spectral dimension reduction
As a novel clustering method, affinity propagation (AP) clustering can identify high-quality cluster centers by passing messages between data points. But its ultimate cluster number is affected by a user-defi...
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Article
A clustering-based failure mode and effect analysis model and its application to the edible bird nest industry
Failure mode and effect analysis (FMEA) is a popular safety and reliability analysis tool in examining potential failures of products, process, designs, or services, in a wide range of industries. While FMEA ...
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Article
Freshwater algal bloom prediction by extreme learning machine in Macau Storage Reservoirs
Understanding and predicting dynamic change of algae population in freshwater reservoirs is particularly important, as algae-releasing cyanotoxins are carcinogens that would affect the health of public. Howeve...
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Article
Manifold regularized extreme learning machine
Extreme learning machine (ELM) works for generalized single-hidden-layer feedforward networks (SLFNs), and its essence is that the hidden layer of SLFNs need not be tuned. But ELM only utilizes labeled data to...
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Article
An adaptive neural networks formulation for the two-dimensional principal component analysis
This study, for the first time, developed an adaptive neural networks (NNs) formulation for the two-dimensional principal component analysis (2DPCA), whose space complexity is far lower than that of its stati...
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Article
Stability analysis of stochastic memristor-based recurrent neural networks with mixed time-varying delays
In this paper, the stability problem of stochastic memristor-based recurrent neural networks with mixed time-varying delays is investigated. Sufficient conditions are established in terms of linear matrix ineq...
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Article
A novel clustering-based image segmentation via density peaks algorithm with mid-level feature
Image segmentation is an important and fundamental task in computer vision. Its performance is mainly influenced by feature representations and segmentation algorithms. In this paper, we propose a novel cluste...
