共查询到20条相似文献，搜索用时 171 毫秒
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针对单一的赤潮特征提取算法在对赤潮遥感图像进行特征提取时还存在准确性不高等问题,本文提出了一种基于多特征的赤潮遥感提取算法,首先对加权平均方法进行改进,提出了自适应加权平均算法,对遥感图像的叶绿素浓度特征进行提取,然后采用偏差系数对水体固有光学模型进行参数优化,对遥感图像的光谱特征进行提取。实例仿真试验结果表明,本文提出的基于多特征的赤潮遥感提取算法相比较单一的光谱特征提取算法,具有较高的赤潮特征提取准确性和稳定性。 相似文献
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机场鸟情预测预报具有复杂性和分布性的特点,传统的面向结构和对象的方法已经不能给出一个描述系统行为以及互相之间信息交换的统一模型。论文采用面向Agent信息系统建模方法将现实世界看做多个具有自主行为的实体,提出了基于多Agent的中国机场鸟情预测预报系统的组织形式,即中央鸟情预测预报管理中心Agent、区域鸟情预测预报管理中心Agent和三级鸟情预测预报管理Agent。详细描述了各个Agent的功能以及之间的工作方式和合作机制,为中国机场鸟情预测预报系统的建立提供了理论依据。 相似文献
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采用不同的损失函数和罚函数构建了广义指数预报因子模型,用该模型来预测国际黄金价格.构建方法包括:1)岭估计方法;2)基于L1、L2以及二者结合的损失函数LM,利用LASSO和SCAD 2种罚函数选取不同参数EWMA的线性组合作为预报因子.实证检验表明,该方法构建的模型有效改进了单参数EWMA预测模型,其预测精度优于已有方法. 相似文献
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由于风力发电依靠的风力具有较大的不可控性,引起风电的加入对电网调度提出了较高的要求,因此对风能进行预测具有十分重要的作用。本文提出了一种基于集成神经网模型的风能预报方法,该方法将传统的单一模型回归预测转变为多种条件多神经网的共同回归预测,并集成回归结果作为风能预测的最终值。实验表明,本文提出的方法提高了预测的精度与稳定性,较传统方法具有更高的实用价值。 相似文献
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浙江海区赤潮发生前期气象因子的统计分析 总被引：6，自引：0，他引：6
本文利用2002年5～6月的赤潮纪录,及逐日的温度、气压和降水等气象要素实测资料。分析了浙江海域赤潮发生前期有关气象要素的变化特点;以及赤潮发生时,不同气象因子分布的统计特征。结果表明：浙江海域赤潮的发生有明显的地域特征,在不同海区,利于赤潮发生的气象条件是不同的。 相似文献
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Surabhi Verma Som Sekhar Bhattacharyya Saurav Kumar 《Information processing & management》2018,54(5):791-806
Research on the adoption of systems for big data analytics has drawn enormous attention in Information Systems research. This study extends big data analytics adoption research by examining the effects of system characteristics on the attitude of managers towards the usage of big data analytics systems. A research model has been proposed in this study based on an extensive review of literature pertaining to the Technology Acceptance Model, with further validation by a survey of 150 big data analytics users. Results of this survey confirm that characteristics of the big data analytics system have significant direct and indirect effects on belief in the benefits of big data analytics systems and perceived usefulness, attitude and adoption. Moreover, there are mediation effects that exist among the system characteristics, benefits of big data analytics systems, perceived usefulness and the attitude towards using big data analytics system. This study expands the existing body of knowledge on the adoption of big data analytics systems, and benefits big data analytics providers and vendors while helping in the formulation of their business models. 相似文献
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《The Journal of High Technology Management Research》2023,34(2):100465
Businesses have begun using IT apps for a variety of reasons in recent years. The rapid advancement of new technologies has opened up vast prospects for businesses to digitise their operations, enhance their use of information systems, and compete more effectively in the global marketplace. Information technology (IT) businesses can benefit greatly from Big Data analytics due to the depth and breadth of their data analysis. Big data can be used to examine IT departments in the following ways: performance analysis, forecast maintenance, security analysis, and resource analysis. When it comes to boosting their business's dependability, speed, quality, and effectiveness, most companies rely on big data. Companies can gain a competitive edge thanks to the massive amounts of data that big data is able to collect, store, and manage. Big data analytics is being used by a growing number of businesses to make sense of their mountain of data. In this paper, we examine the ways in which IBM, TCS, and Cognizant use big data within their operations. Long-term planning strategies and business intelligence practises are also suggested in this research as means of protecting personal information. 相似文献
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针对赤潮生物提出具有较高准确率的实时自动分类方法,本文提出采用ReliefF-SBS进行特征选择,即针对赤潮生物图像原始数据集进行特征分析,并在此基础上,对原始特征集进行特征选择以去除特征集中的无关特征和冗余特征,得到最优特征子集,减少它们对分类器分类精度的影响。文中给出了实验结果和分析,同时验证了对k-Nearest Neighbor algorithm(KNN)和Support Vector Machine(SVM)分类器分类效果的影响。 相似文献
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TC灾情评估分析及减灾对策 总被引：2，自引：0，他引：2
对比分析0216号台风Sinlaku、9417号台风Fred、9909号热带风暴Wendy等20世纪90年代以来3个“著名”热带气旋（TC）对温州造成的灾情评估指数和灾情指数,发现：Sinlaku的灾情指数大大低于同样在温州登陆、同样时逢天文大潮、强度、路径相似、灾情评估指数相近的台风Fred的灾情指数,甚至明显低于灾情评估指数定义为中灾的9909号热带风暴Wendy。说明气象预报的准确及时与科学的防御减灾措施可以非常有效地降低自然灾害造成的经济损失及对社会发展的负面影响。文中提出了一些减灾对策,可供政府和有关部门参考。 相似文献
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The mechanism of business analytics affordances enhancing the management of cloud computing data security is a key antecedent in improving cloud computing security. Based on information value chain theory and IT affordances theory, a research model is built to investigate the underlying mechanism of business analytics affordances enhancing the management of cloud computing data security. The model includes business analytics affordances, decision-making affordances of cloud computing data security, decision-making rationality of cloud computing data security, and the management of cloud computing data security. Simultaneously, the model considers the role of data-driven culture and IT business process integration. It is empirically tested using data collected from 316 enterprises by Partial Least Squares-based structural equation model. Without data-driven culture and IT business process integration, the results suggest that there is a process from business analytics affordances to decision-making affordances of cloud computing data security, decision-making rationality of cloud computing data security, and to the management of cloud computing data security. Moreover, Data-driven culture and IT business process integration have a positive mediation effect on the relationship between business analytics affordances and decision-making affordances of cloud computing data security. The conclusions in this study provide useful references for the enterprise to strengthen the management of cloud computing data security using business analytics. 相似文献
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The number of firms that intend to invest in big data analytics has declined and many firms that invested in the use of these tools could not successfully deploy their project to production. In this study, we leverage the valence theory perspective to investigate the role of positive and negative valence factors on the impact of bigness of data on big data analytics usage within firms. The research model is validated empirically from 140 IT managers and data analysts using survey data. The results confirm the impact of bigness of data on both negative valence (i.e., data security concern and task complexity), and positive valence (i.e., data accessibility and data diagnosticity) factors. In addition, findings show that data security concern is not a critical factor in using big data analytics. The results also show that, interestingly, at different levels of data security concern, task complexity, data accessibility, and data diagnosticity, the impact of bigness of data on big data analytics use will be varied. For practitioners, the findings provide important guidelines to increase the extent of using big data analytics by considering both positive and negative valence factors. 相似文献
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Felix M. Simon 《The Information Society》2019,35(3):158-169
Data-driven campaigning has been in the spotlight over several years. Yet, we still have a limited understanding of political data analytics companies: how they envision data analytics and voter targeting, their role in electoral processes and what promises they make to their clients. This article focuses on the way in which such issues are conceived of in the marketing rhetoric of the political data analytics industry. Drawing on a sample of 19 political data analytics companies it systematically explores the ways in which data analytics is envisioned and marketed as a powerful tool in electoral processes, exposing a fundamental disconnect between scholarly discourse on the one hand – often critical of the claims of these companies about the efficacy of their methods – and a highly functionary data imaginary on the other hand, actively fostered by the political data-analytics industry and the media. 相似文献