In response to the increasing severity of hazy weather and the difficulty of prediction, an SSA-SVR based PM2.5 content prediction method is proposed. Specifically, the excellent search capability of the Sparrow Search Algorithm (SSA) was utilized to search for the optimal parameter combinations for the Support Vector Regression (SVR) machine. Firstly, the meteorological factors are dimensionalized using factor analysis. Then the prediction effect of PM2.5 in Beijing is experimentally compared with the regression model constructed by other algorithms. The results show that SSA has stable global search performance and can effectively reduce the influence of SVR parameter selection on the generalization ability and regression accuracy of the system. This is useful for monitoring and prevention of haze and so on.
Picture division has a special meaning for computer visualization and schema identification. Fast target extraction from deterministic images is an important problem facing real-time picture manipulation. Traditional areal models rely on globally converged messages to achieve fault-minimized segmentation. Its image segmentation is ineffective and takes up a lot of time. To address this problem, this paper proposes a model that Fast Region Image Segmentation of the Least Squares (FRISLS). Specifically, the target as well as the backdrop of the primary picture is approximated by just a pair of constants in order to establish the minimum error function. The weight matrix is used to reduce the influence of the background on image segmentation, and least squares are introduced to achieve fast convergence of the model. Through comparison with other area model-based approaches, it is validated the effectiveness of the study. The results indicate that this method ensures high precision of picture division, and enhances the performance of picture splitting efficiency.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.