80 Result(s)
within
**-**a Ding
Artificial Intelligence
Computational Intelligence
Mathematical Logic and Foundations
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Article
An iterative stacked weighted auto-encoder
The training of stacked auto-encoders (SAEs) consists of an unsupervised layer-wise pre-training and a supervised fine-tuning training. The unsupervised pre-training greedily learns internal data representatio...
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Article
A novel prediction method of complex univariate time series based on k-means clustering
Time-series prediction has been widely studied and applied in various fields. For the time series with high acquisition frequency and high noise, it is very difficult to establish a prediction model directly. ...
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Article
Feature selection based on hybridization of genetic algorithm and competitive swarm optimizer
Feature selection is one of the hottest machine learning topics in recent years. The main purposes of it are to simplify the original model, improve the readability of the model, and prevent over-fitting by se...
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Article
Open AccessFault tolerant control for nonlinear systems using sliding mode and adaptive neural network estimator
This paper proposes a new fault tolerant control scheme for a class of nonlinear systems including robotic systems and aeronautical systems. In this method, a sliding mode control is applied to maintain system...
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Article
A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices
Portfolio optimization is one of the most important problems in the finance field. The traditional Markowitz mean-variance model is often unrealistic since it relies on the perfect market information. In this ...
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Article
Green fresh product cost sharing contracts considering freshness-kee** effort
Nowadays, along with increased public demands on the high-quality green fresh product, the downstream retailer has to spend in the packaging and cold chain transportation and the upstream farmer needs to inves...
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Article
Green investment in a supply chain based on price and quality competition
Along with the significant improvement of environmental consciousness, consumers not only consider the price and quality level of products, but also pay more attention to their green level. In order to strengt...
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Article
Active constraint spectral clustering based on Hessian matrix
Applying the pairwise constraint algorithm to spectral clustering has become a hot topic in data mining research in recent years. In this paper, a clustering algorithm is proposed, called an active constraint ...
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Article
Open AccessResearch on National Pattern Reuse Design and Optimization Method Based on Improved Shape Grammar
Considering the low degree of abstraction of traditional shape grammar in national pattern reuse design, this paper proposes a method based on the combination of improved shape grammar and an optimization algo...
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Article
Centroid opposition with a two-point full crossover for the partially attracted firefly algorithm
The firefly algorithm (FA) is a powerful optimization tool. However, the existing FA and its variants seldom take advantage of intermediate data generated during algorithm iteration. In this paper, the centroi...
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Article
Correction to: An extended prospect theory–VIKOR approach for emergency decision making with 2-dimension uncertain linguistic information
The first author name was incorrectly published. The correct name has been copied below:
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Article
Uncertain random simulation algorithm with application to bottleneck assignment problem
Uncertain random simulation plays an important role in solving uncertain random optimization problems that include random variables and uncertain variables. In this paper, an uncertain random simulation is pro...
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Article
L1-norm loss-based projection twin support vector machine for binary classification
This paper presents a L1-norm loss-based projection twin support vector machine (L1LPTSVM) for binary classification. In the pair of optimization problems of L1LPTSVM, L1-norm-based losses are considered for two ...
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Article
An extended prospect theory–VIKOR approach for emergency decision making with 2-dimension uncertain linguistic information
Emergency situations often require high-quality decisions which have to be made within a short period of time. An emergency event is often complex and can cause huge loss of lives and property if a wrong decis...
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Article
BEMD image fusion based on PCNN and compressed sensing
Bidimensional empirical mode decomposition (BEMD) is a new method for multi-scale image decomposition. In order to forbid useless information to cause an adverse impact on results and make the process have a b...
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Article
Object tracking via dense SIFT features and low-rank representation
In this paper, we present a low-rank sparse tracking method which builds upon the particle filtering framework. The proposed method learns the local dense scale-invariant feature transform features correspondi...
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Article
An unsupervised and robust validity index for clustering analysis
The evaluation of clustering results plays an important role in clustering analysis and usually is completed by a validity index or several. But currently existing validity indexes are supervised since they gr...
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Article
A unified incremental reduction with the variations of the object for decision tables
Attribute reduction is one of the issues in the rough set theory, and many reduction algorithms have been proposed to process the static decision systems. However, in real-life applications, the object may var...
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Article
A feasible density peaks clustering algorithm with a merging strategy
Density peaks clustering (DPC) algorithm is a novel algorithm that efficiently deals with the complex structure of the data sets by finding the density peaks. It needs neither iterative process nor more parame...
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Article
A time series forecasting based on cloud model similarity measurement
In this paper, a local cloud model similarity measurement (CMSM) is proposed as a novel method to measure the similarity of time series. Time series similarity measurement is an indispensable part for improvin...
