The nonlinear Kaczmarz method was recently proposed to solve the system of nonlinear equations. In this paper, we first discuss two greedy selection rules, i.e., the maximum residual and maximum distance rules, for the nonlinear Kaczmarz ...

Edge-preserving image smoothing plays a vital role in the field of computational photography. In this paper, we propose a weighted and truncated $L_1$-regularized optimization model for image smoothing. We show that the weighted and truncated scheme ...

In this paper, we prove the representation defects of a cascaded convolutional decoder1 network, considering the capacity of representing different frequency components of an input sample. We conduct the discrete Fourier transform on each channel of the ...

Many real-world problems can be considered multimodal optimization problems (MMOPs), which require locating as many global optima as possible and refining the accuracy of the found optima as high as possible. However, there are some ...

• This paper proposes a strengthening evolution-based differential evolution algorithm with a prediction strategy (SEDE-PS) to better deal with MMOPs.

Robustness and safety concerns of perception systems are of great importance for autonomous vehicle navigation applications. Recent researches demonstrate that the surrounding dynamic object detection results of current perception systems can be easily ...

With the boom in Internet techniques and computer science, a variety of big data have been introduced into forecasting research, bringing new knowledge and improving prediction models. This paper is the first attempt to conduct a ...

• A review on full-scale big data in forecasting research is presented.
• Big data ...

Due to the wide application of cognitive wireless network, the network structure is becoming more and more complex. It is difficult to establish the corresponding mathematical model to simulate the high complexity network environment. The algorithm based ...

Objective. The target of the present paper was to reveal the influence of LncRNA BC083743 on osteogenesis in human bone marrow mesenchymal stem cells (hBMSCs). Methods. Serum specimens from osteoporotic patients and normal subjects were collected to ...

Generally, there is a certain correlation between the level of higher education and the public mental health of college students. Traditionally, questionnaires and literature research methods are used to analyze the correlation between mental health and ...

To address the drawback of single machine learning prediction model which cannot capture the complex hidden factors of crude oil price, ensemble learning method has been widely verified as an excellent solution for crude oil price forecasting. In ...

• The fundamental problem-whether to produce green product, which has been ignored by extant research, is analyzed.

Facing environment-concern consumers, a conventional manufacturer who produces only brown product and sells the product through a downstream retailer is confronted with the problem of whether to introduce green product into the market ...

The success of stock selection is contingent upon the future performance of stock markets. We incorporate stock prediction into stock selection to specifically capture the future features of stock markets, thereby forming a novel ...

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• A novel stock selection method is proposed by introducing stock prediction.
• It ...

An EEMD-based multi-scale fuzzy entropy approach is proposed to analyze the complexity characteristics of clean energy markets.The divide and conquer strategy is introduced to provide a more comprehensive complexity measurement tool for both the overall ...

Display Omitted An LSSVR ensemble learning paradigm with uncertain parameters is proposed.The user-defined parameters in LSSVR are treated as uncertain variables.Uncertain parameters are first used to formulate diverse individual members.Uncertainties ...

Cloudlet is a new paradigm in mobile cloud computing to provide resources to nearby mobile users via one-hop wireless connections. In this study, we leverage the social tie structure among mobile users to achieve mutual-beneficial computation offloading ...

In order to effectively model crude oil spot price with inherently high complexity, a hybrid learning paradigm integrating least squares support vector regression (LSSVR) with a hybrid optimization searching approach for the parameters selection in the ...

As one of the most important energy resources, an accurate prediction for crude oil price can effectively guarantee a rapid new production development with higher production quality and less production cost. Accordingly, a novel decomposition-and-...

We consider a bistatic radar sensor network that consists of multiple separated radar transmitters and radar receivers, which are deployed to detect targets among a set of points of interest. Any transmitter-receiver pair with the same frequency forms a ...

This paper proposes an integrated nonlinearityexploration approach to discover the nonlinearitycharacteristic in clean energy stock market, integrating a set ofdata characteristics analysis technologies. In the proposedapproach, the stock data are first ...

A novel time series forecasting approach with consideration of inner knowledge hidden in data, in terms of data characteristics, is proposed. In the proposed methodology, the main data characteristics hidden in the observed time series data are first ...