排序方式： 共有37条查询结果，搜索用时 15 毫秒
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针对古漆器漆膜数据类间不平衡、样本规模小,以及传统机器学习算法分类效果较差的问题,提出一种改进SMOTE的过采样方法改变漆器漆膜数据样本分布,使其达到平衡。该方法通过比较各类样本间的欧式距离,删除了人工样本中的噪声数据,然后运用集成学习中的随机森林算法进行分类,提高了少数类的分类准确率。UCI数据集上的实验结果表明,改进的过采样方法性能更优,评价指标F1-score与AUC值分别得到2%、5%以上的提升。结合改进的过采样方法与机器学习算法进行对比实验,结果证明,随机森林算法精度更高,在对古漆器年代的判别中,随机森林算法的F1-score与AUC值高达87.76%、89.34%。 相似文献
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《Information processing & management》2022,59(1):102739
Digital information exchange enables quick creation and sharing of information and thus changes existing habits. Social media is becoming the main source of news for end-users replacing traditional media. This also enables the proliferation of fake news, which misinforms readers and is used to serve the interests of the creators. As a result, automated fake news detection systems are attracting attention. However, automatic fake news detection presents a major challenge; content evaluation is increasingly becoming the responsibility of the end-user. Thus, in the present study we used information quality (IQ) as an instrument to investigate how users can detect fake news. Specifically, we examined how users perceive fake news in the form of shorter paragraphs on individual IQ dimensions. We also investigated which user characteristics might affect fake news detection. We performed an empirical study with 1123 users, who evaluated randomly generated stories with statements of various level of correctness by individual IQ dimensions. The results reveal that IQ can be used as a tool for fake news detection. Our findings show that (1) domain knowledge has a positive impact on fake news detection; (2) education in combination with domain knowledge improves fake news detection; and (3) personality trait conscientiousness contributes significantly to fake news detection in all dimensions. 相似文献
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Meng-Jie Hu Jiang-Wen Xiao Ren-Bin Xiao Wu-Hua Chen 《Journal of The Franklin Institute》2017,354(10):4034-4054
This study addresses the exponential stability and positive stabilization problems of impulsive positive systems (IPSs) with time delay. Specially, three types of impulses, namely, disturbance, “neutral”, and stabilizing impulses, are considered. For each type of impulsive effect, the exponential stability criterion is established utilizing the Lyapunov–Razumikhin techniques. Moreover, on the basis of the obtained stability results, the state-feedback controller design problem is investigated to positively stabilize the IPSs with time delay under different types of impulsive effects. Finally, numerical examples are provided to illustrate the effectiveness of the theoretical results. 相似文献
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跨产业间的技术融合已成为诱发新兴产业形成并提升其绩效的重要因素。利用EPO-PATSTAT数据库搜索出生物芯片产业13101项专利数据,利用Datastream、Osiris、Amadeus企业数据库搜集335家生物芯片企业财务数据。运用N指数、辛普森多样性指数和香农-维纳指数方法,依据专利数据,测算生物芯片产业技术融合宽度和深度。采用面板数据的GLS回归方法,依据2001-2013年间生物芯片产业20个样本企业专利数据和财务数据,实证分析技术融合引发新型竞争协同关系最终提升战略性新兴产业绩效的机理。研究表明:技术融合度对产业绩效有明显的提升作用,同时提高技术融合的宽度与深度更能带动产业发展;产业融合创新对产业绩效的作用机制随着产业的成长趋势呈现一条开口向下的"倒U型"曲线。这一研究具有重要的政策启示:放松产业管制,加强跨产业共性技术研发,促进跨产业间的技术融合,强化跨产业间的新型竞争协同关系,更有利于战略性新兴产业的规模扩大和绩效提升。 相似文献
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不同干旱程度下外源茉莉酸甲酯对水稻抗旱性的影响 总被引：1，自引：0，他引：1
茉莉酸甲酯（MeJA）是与抗性密切相关的植物生长物质,本研究探讨了它在不同干旱程度的胁迫条件下,施加不同浓度的MeJA对水稻抗旱性的诱导效应。结果表明,随着水分胁迫的加深,水稻遭受伤害随之加剧,水稻叶片中各生理生化指标均有相应的变化,叶片水势,丙二醛MDA含量,电导率及脂氧合酶（LOX）活性都显著增加。施加MeJA后,水稻遭受胁迫的程度有所缓解,不过在高度干旱情况下,MeJA并不能使水稻完全恢复到对照水平,水稻仍然遭受一定程度的伤害,其中,浓度较小（0．25μM）的MeJA处理使水稻恢复较多,可以认为是增强水稻抗旱性的较适宜浓度。 相似文献
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《Information processing & management》2020,57(6):102299
Recent advances in semantic web have shown how entity related searches have benefited from entity-based knowledge graphs. However, much of the commonsense knowledge about the real world is in the form of procedures or sequences of actions. Also, search log analysis shows that ‘how-to queries’ make up a significant amount of users’ queries. Unfortunately, these kinds of knowledge are missing from most knowledge graphs and commonsense knowledge bases in use. To empower semantic search, and other intelligent applications, computers need a much broader understanding of the world properties of everyday objects, human activities, and more. Luckily, such knowledge is abundantly available on-line and can be accessed from how-to communities. One domain of interest by on-line communities is the health domain, whereby users usually seek home remedies to common health-related issues. An example of such queries might be ‘how to stop nausea using acupressure’ or ‘how to aid digestion naturally’. To answer such questions, we need systems that understand natural language and knowledge bases with task frames of solutions in a holistic approach, including the tools required, the agents involved, and the temporal order of the actions. Our goal is to construct a machine-readable domain targeted high precision procedural knowledge base containing task frames. We developed a pipeline of methods leveraging open information extraction tool to extract procedural knowledge by tapping into on-line communities. Also, we devised a mechanism to canonicalize the task frames into clusters based on the similarity of the problems they intend to solve. The resulting know-how knowledge base, HealthAidKB, consists of more than 71 K task frames which are structured hierarchically and categorically; and can be used in many applications such as semantic search, digital personal assistants, human-computer dialog and computer vision. A comprehensive evaluation of our knowledge base shows high accuracy. 相似文献
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《Journal of The Franklin Institute》2019,356(17):10196-10215
This paper deals with the large category of convex optimization problems on the framework of second-order multi-agent systems, where each distinct agent is assigned with a local objective function, and the overall optimization problem is defined as minimizing the sum of all the local objective functions. To solve this problem, two distributed optimization algorithms are proposed, namely, a time-triggered algorithm and an event-triggered algorithm, to make all agents converge to the optimal solution of the optimization problem cooperatively. The main advantage of our algorithms is to remove unnecessary communications, and hence reduce communication costs and energy consumptions in real-time applications. Moreover, in the proposed algorithms, each agent uses only the position information from its neighbors. With the design of the Lyapunov function, the criteria about the controller parameters are derived to ensure the algorithms converge to the optimal solution. Finally, numerical examples are given to illustrate the effectiveness of the proposed algorithms. 相似文献
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《Journal of The Franklin Institute》2022,359(12):6503-6522
This paper focuses on the dynamic event-based recursive filtering problem for a class of time-varying networked systems under the encoding-decoding mechanism. For the purpose of saving energy consumption, a dynamic event-triggered protocol is applied to determine whether the measurement of the sensor is transmitted or not. In the transmission process of the measurement, a dynamic-quantization-based encoding-decoding mechanism is introduced to encrypt the transmitted measurement. In specific, the measurement outputs are first encoded into codewords which are then transmitted from the encoder to the decoder. After received by the decoder, the codewords are first decoded and then sent to the filter. A bounded uncertainty is introduced to characterize the difference between the original measurement and the decoded measurement. This paper is devoted to developing a recursive filtering algorithm for the considered system such that a minimal upper bound on the filtering error covariance is derived through appropriately designing filter gain. Moreover, the mean-square exponential boundedness of the filtering error is analyzed. Finally, the efficiency and superiority of the proposed algorithm are verified through two simulation examples. 相似文献