考虑CEEMDAN样本熵和SVR的短期风速预测

为降低由于风速信号的非线性和非平稳性带来的风速预测难度，提高短期风速预测的准确性，提出一种考虑样本熵的组合分解模式和支持向量回归（SVR）相结合的预测模型。首先采用自适应噪声的完全集合经验模态分解（CEEMDAN）方法分解风速历史数据，并计算各模态分量的样本熵；然后采用变分模态分解（VMD）方法对样本熵最大的模态分量进行二次分解，充分削弱风速分量的非平稳性；接着对分解得到所有模态分量分别建立SVR预测模型；最后将各分量的预测值求和完成最终风速预测。实例分析表明，所提模型对比其他模型的预测误差最小，预测精度最高，可有效预测短期风速。     

大断面切眼支护技术研究与实践

针对古城煤矿S1303综采工作面切眼的地质构造与施工条件,提出了大断面切眼采用“锚网索+π型梁棚+预注浆”联合支护方案,有效地控制了大断面切眼留顶煤施工期间的支护难题,保障了S1303综采面切眼能够满足设计要求和如期完成施工,为同类条件下的切眼施工提供了一定参考。     

基于SARIMA-GRNN-SVM的短期商业电力负荷组合预测方法

针对短期商业电力负荷预测准确性与周期难以满足现有电力现货市场的问题,提出了一种基于SARIMAGRNN-SVM(seasonal autoregressive integrated moving average-generalized regression neural network-support vector machine)的商业电力负荷组合预测模型。首先,对商业电力负荷变化的周期规律与随机因素的复杂影响进行了分析;然后,结合以上分析,选用SARIMA和GRNN为单一预测模型对商业电力负荷进行预测,并利用SVM进行组合,实现日前商业电力负荷预测;最后,通过某商业综合体的电力负荷数据进行验证。所提组合预测模型较单一预测模型拥有更优的预测精度与鲁棒性,可以为短期商业电力负荷预测提供借鉴。     

A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

User-friendly search interface for older adults: supporting search goal refreshing in working memory to improve information search strategies

ABSTRACT

This study investigates how a search interface that displays users’ ultimate query (i.e. users’ current search goal) can cope with the age-related decrease of fluid abilities and support older users’ search behaviours. 30 young and 18 older adults completed 9 search problems with a regular web browser or with the experimental search interface. Results showed that older adults spent longer time on the search engine result pages, they needed more time to reformulate, and they had more difficulties exploring the search paths elaborated. Age-differences also appeared as soon as the beginning of the search. The support tool helped older users reformulate their queries more rapidly and elaborate more flexible search strategies at the beginning of the activity. Indeed, older adults who interacted with the support tool switched to the processing of a new search path more rapidly instead of exploiting their initial query (i.e. they visited fewer websites for the initial query produced and reformulated a query instead of keeping on conducting a deeper investigation of the search results provided in the search engine result page). Implications of these findings for the design of effective support tools for older users are discussed.     

An Innovative Non-Pillar Coal-Mining Technology with Automatically Formed Entry: A Case Study

A non-pillar coal-mining technology with an automatically formed entry is proposed, which reduces the waste of coal resources and the underground entry drivage workload. Three key techniques in this technology cooperate to achieve automatic formation and retaining of the gob-side entry, and to realize non-pillar mining. Constant-resistance large deformation (CRLD) support ensures the stability of the entry roof; directional presplitting blasting (DPB) separates the entry roof and the gob roof; and a blocking-gangue support system (BGSS) integrates the caved rock material as an effective entry rib. An industrial test was conducted to verify the engineering effects of these key techniques. The field application results showed that the retained entry was under the pressure-relief zone due to the broken-expansion nature of the caved rock mass within the DPB height. After going through a provisional dynamic pressure-bearing zone, the retained entry entered the stability zone. The final stable entry meets the requirements of safety and production. The research results demonstrate the good engineering applicability of this technology. By taking the framework of the technology design principles into consideration and adjusting the measures according to different site conditions, it is expected that the proposed non-pillar coal-mining technology can be popularized on a large scale.     

Test sample allocation method for testability verification test

An extended failure mode effect and criticality analysis (FMECA)-based sample allocation method for testability verification is presented in this study to deal with the poor representativeness of test sample sets and the randomness of the testability evaluation results caused by unreasonable selection of failure samples. First, the fault propagation intensity is introduced as part of the extended information of FMECA, and the sample allocation impact factors of component units and failure modes are determined under this framework. Then, the failure mode similarity and impact factor support are defined, and the game decision method for weighing the relationship between similarity and support is proposed to obtain the weight of failure mode impact factor. Finally, a two-step allocation framework of test samples is formulated to realize the sample allocation of component units and failure modes. This method is applied to the testability verification test of a launch control system. Results show that this method can obtain more representative test samples compared with the traditional sample allocation method while effectively reducing randomness of single testability evaluation result.     

云岗矿极近距离煤层安全开采采掘技术研究

为防止311盘区11-2^#层工作面掘进及采煤过程中造成近距离煤层的漏顶事故发生,通过优化工作面布置方式、掘进期间支护形式及参数,制定工作面开采期间的回采工艺及顶板管理措施,在生产实践过程中总结了一套安全可靠的极近距离煤层采掘技术,对近距离煤层开采有一定的指导意义。     

基于SVM的煤与瓦斯突出预测模型及应用

为有效预测矿井内煤与瓦斯突出的危险程度,对其影响因素做了分析与探讨,分别构建了基于粒子群优化算法以及遗传算法支持向量机的煤与瓦斯突出预测模型,并且通过实例对两种模型预测的准确性进行了验证。分别利用单项以及综合指标、BP神经网络以及PSO-SVM模型、GA-SVM模型,对寺河煤矿二号井的突出区域进行预测比较。结果表明,PSO-SVM的预测模型不仅可以在小样本数据中预测出煤与瓦斯突出程度的大小,而且综合预测结果更加精确,其在解决矿井内煤与瓦斯突出的小样本数据中显示出更加强大、通用的性能。     

复杂膨胀性围岩条件下交岔点支护技术研究

针对复杂膨胀性围岩条件下交岔点高应力集中区围岩稳定性控制和支护技术难题，通过对交岔点围岩变形表现形式、交岔点围岩变形机理的研究分析，提出了交岔点支护难点及重点。基于围岩控制理论分析，提出了“有限让压的柔性支护+全断面封闭抗压的刚性支护技术”，前期柔性支护采用“高强、高预应力锚杆+锚索+喷浆”联合支护有限度控制围岩变形，允许围岩在可控范围内释放围岩应力|后期通过架设异形支架与支撑架组成的联合支护体并喷射混凝土对交岔点围岩进行全断面封闭抗压支护，有效控制巷道交岔点围岩的变形。确保了交岔点围岩变形的整体可控性、稳定性，达到了预期支护效果。