双碳及能源安全背景下中国电煤月度需求组合预测

双碳发展背景下,准确及时的电煤需求预测有利于国家制定电煤供需计划及能源安全供给。现有研究对电煤月度需求预测的较少,且精度欠佳,难以保证电煤月度需求感知的及时性和准确性。提出由回归加权融合反向传播神经网络、门控循环单元网络和长短期记忆网络的组合预测模型预测我国电煤月度需求。首先采用格兰杰因果检验从月度经济及能源生产因素中筛选显著影响电煤需求的变量。然后构建单一及组合模型进行预测,其中,组合模型权重由回归计算得到。结果表明,相较单一模型,组合预测模型在电煤需求预测中性能更好。     

基于多通道脑电信号的因果网络情绪识别

情绪是由大脑内多个通道共同作用产生的,格兰杰因果检验作为情绪识别的主流方法,在计算任意2个通道之间的因果关系时容易忽略其他通道的影响。面向多通道脑电信号,提出一种基于条件格兰杰因果检验（CGC）的因果网络情绪识别方法。利用CGC算法计算不同情绪下大脑全通道的因果关系,据此构建因果网络,并通过分析各通道的入/出度和介数拓扑属性找到关键通道,得到简化的因果网络进行情绪识别。将节点之间的因果连接关系作为特征分别输入SVM和KNN分类器进行分类训练,实验结果表明,简化网络的识别率分别为75.3%和78.4%,验证了所提方法的有效性。     

基于TRIZ解决航空航天用吸波贴片成本高的问题

目的 解决隐身飞机在飞行过程中因吸波贴片自身过重产生巨大的飞行成本,吸波贴片在飞行条件下易产生划痕、损伤、材料损耗快,以及因修复工序复杂、耗时长产生大量维护费用等问题。方法 应用TRIZ理论进行分析求解,通过采用功能模型分析、因果分析等找到航空航天用吸波贴片成本高的关键缺陷,利用技术矛盾分析、物理矛盾分析、物场模型及标准解、小人法等工具得到多个解决方案。经过综合评估最终找到经济、易于实现的解决方案。结果 通过运用TRIZ理论,并且通过综合评价找到了减少吸波贴片成本的最优方案：吸波贴片中的吸波体由掺杂杂原子的石墨烯构成了多孔结构,增加了其吸波性能;再将材料与自愈合材料相结合,增加其自愈能力,从而得到吸波性能好、质量小、自愈合能力强的吸波贴片。结论 文中得出的结果对减少隐身战机吸波贴片成本的研究具有一定的理论指导意义,有助于减少高集成设备过多对人类及环境产生的危害。     

Fusion ANFIS models based on multi-stock volatility causality for TAIEX forecasting

Stock market investors value accurate forecasting of future stock price from trading systems because of the potential for large profits. Thus, investors use different forecasting models, such as the time-series model, to assemble a superior investment portfolio. Unfortunately, there are three major drawbacks to the time-series model: (1) most statistical methods rely on some assumptions about the variables; (2) most conventional time-series models use only one variable in forecasting; and (3) the rules mined from artificial neural networks are not easily understandable. To address these shortcomings, this study proposes a new model based on multi-stock volatility causality, a fusion adaptive-network-based fuzzy inference system (ANFIS) procedure, for forecasting stock price problems in Taiwan. Furthermore, to illustrate the proposed model, three practical, collected stock index datasets from the USA and Taiwan stock markets are used in the empirical experiment. The experimental results indicate that the proposed model is superior to the listing methods in terms of root mean squared error, and further evaluation reveals that the profits comparison results for the proposed model produce higher profits than the listing models.     

基于干预规则挖掘因果关系与分段干预事件及对比不等式

为揭示亚复杂系统(SCS)在干预下的特殊行为,提出了对比不等式概念,提出并实现了分段干预规则的挖掘算法;通过在亚复杂系统中施加扰动式干预并分析其动力学效应,提出并实现了基于扰动因果关系挖掘算法。在真实数据上的实验表明,分段干预规则发现了传统挖掘方法难以发现的新干预事件,因果挖掘算法发现了传统方法难以发现的因果关系。     

含约束的基于模型的诊断系统

在诊断空间中如何选取理想诊断是诊断系统面临的一个重要问题。在实际的诊断过程中,人们会利用限制条件排除不太可能的诊断,或者利用强制条件选取较优的诊断。按照这个思想,作者提出含约束的基于模型的诊断系统,通过增加依赖于应用领域的约束控制诊断空间,这是一种能够融入计算过程的选择诊断的机制,同时作者在系统拓扑结构的基础上给出了选取理想约束的理论依据。     

我国留学生人数的预测及其对居民消费的影响

采用1985—2012年数据,利用时间序列分析方法,建立了刻画我国出国留学人数变动的模型ARIMA(2,2,2),得到较好的预测效果.同时研究了出国留学人数与我国城镇居民人均消费性支出之间的关系,建立了相应的模型,并进行了Granger因果关系检验.结果表明:出国留学生数的对数每增加1%,城镇居民人均消费性支出的对数将增加近0.06%.     

广东省电网建设与经济发展关系实证研究

以广东省1993--2011年相关时间序列数据为基础,建立了反映电网建设水平与社会经济发展关系的向量自回归（VAR）模型,在VAR模型的基础上,分析了广东省电网建设指标与社会经济发展指标的格兰杰因果关系,运用脉冲响应函数和方差分解方法分析了电网建设与社会经济发展之间的动态影响。研究结果表明,电网建设是经济增长的基础条件之一,在电网建设与经济增长的相互作用中,电网建设对经济增长的促进作用更为显著。     

Dissociating Processes Supporting Causal Perception and Causal Inference in the Brain.

An understanding of relations between causes and effects is essential for making sense of the dynamic physical world. It has been argued that this understanding of causality depends on both perceptual and inferential components. To investigate whether causal perception and causal inference rely on common or on distinct processes, the authors tested 2 callosotomy (split-brain) patients and a group of neurologically intact participants. The authors show that the direct perception of causality and the ability to infer causality depend on different hemispheres of the divided brain. This finding implies that understanding causality is not a unitary process and that causal perception and causal inference can proceed independently. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Built environment,causality and urban planning

Informed by critical realist philosophy of science, this paper aims to contribute to a better understanding of the issue of causality within urban and planning research. The concept of causality dominating within certain influential disciplinary and philosophical traditions is difficult to reconcile with research into influences of the built environment on human actions. This paper promotes a conceptualizing of causality in terms of generative mechanisms operating in different combinations in normally non-closed systems, and discusses in what sense the built environment can be said to exert causal influences on human actions. In order to integrate knowledge about causal influences at the level of the individual and at the city level, a combination of qualitative and quantitative research methods is recommended.