智能电网中D2D网络的通信资源管理优化方案

当前在智能电网的应用中,各种智能终端的使用,使得移动数据流量空前增长,电力互联方式在面临海量数据传输的需求时,由于资源受限,信道间会产生一定的干扰,从而影响通信质量。为了解决通信资源管理这一问题,与常见的移动边缘计算(MEC)方法不同,文中提出了一种网络资源分配方法,优化链路选择和子信道分配,以实现能量效率的最大化。仿真结果表明,与没有卸载和部分优化的方法相比,此方法在能效方面有了很大的提高。     

基于跨临界CO2热泵的茶叶生产能源系统负荷削减潜力

乡村产业中的化石能源设备逐渐被电能技术替代，引起了乡村负荷波动增大、部分时段产生集中高负荷的问题。为了解决以上问题，将低品位清洁能源应用至乡村的茶叶生产中，针对烘茶全过程的工艺要求提出了跨临界CO₂热泵烘茶技术；并以某茶叶生产乡村为对象，对其代表台区的全年日用电量及产茶日负荷进行了分析，得出采用CO₂热泵烘茶后其负荷得到大幅度削减，整体可降低至原负荷的39.6%~46.8%，峰值负荷与平时负荷的比值由原本的13.6降至5.4~6.2。跨临界CO₂热泵应用至农产品生产中可有效缓解乡村供电压力。     

Grid Search for Predicting Coronary Heart Disease by Tuning Hyper-Parameters

Diagnosing the cardiovascular disease is one of the biggest medical difficulties in recent years. Coronary cardiovascular (CHD) is a kind of heart and blood vascular disease. Predicting this sort of cardiac illness leads to more precise decisions for cardiac disorders. Implementing Grid Search Optimization (GSO) machine training models is therefore a useful way to forecast the sickness as soon as possible. The state-of-the-art work is the tuning of the hyperparameter together with the selection of the feature by utilizing the model search to minimize the false-negative rate. Three models with a cross-validation approach do the required task. Feature Selection based on the use of statistical and correlation matrices for multivariate analysis. For Random Search and Grid Search models, extensive comparison findings are produced utilizing retrieval, F1 score, and precision measurements. The models are evaluated using the metrics and kappa statistics that illustrate the three models’ comparability. The study effort focuses on optimizing function selection, tweaking hyperparameters to improve model accuracy and the prediction of heart disease by examining Framingham datasets using random forestry classification. Tuning the hyperparameter in the model of grid search thus decreases the erroneous rate achieves global optimization.     

A hybrid optimization technique for proficient energy management in smart grid environment

Electrical energy is one of the key components for the development and sustainability of any nation. India is a developing country and blessed with a huge amount of renewable energy resources still there are various remote areas where the grid supply is rarely available. As electrical energy is the basic requirement, therefore it must be taken up on priority to exploit the available renewable energy resources integrated with storage devices like fuel cells and batteries for power generation and help the planners in providing the energy-efficient and alternative solution. This solution will not only meet electricity demand but also helps reduce greenhouse gas emissions as a result the efficient, sustainable and eco-friendly solution can be achieved which would contribute a lot to the smart grid environment. In this paper, a modified grey wolf optimizer approach is utilized to develop a hybrid microgrid based on available renewable energy resources considering modern power grid interactions. The proposed approach would be able to provide a robust and efficient microgrid that utilizes solar photovoltaic technology and wind energy conversion system. This approach integrates renewable resources with the meta-heuristic optimization algorithm for optimal dispatch of energy in grid-connected hybrid microgrid system. The proposed approach is mainly aimed to provide the optimal sizing of renewable energy-based microgrids based on the load profile according to time of use. To validate the proposed approach, a comparative study is also conducted through a case study and shows a significant savings of 30.88% and 49.99% of the rolling cost in comparison with fuzzy logic and mixed integer linear programming-based energy management system respectively.     

新型地锚张弦梁式泥石流格栅坝构件受力的简化计算方法

针对常见泥石流防治结构被冲击破坏的问题，基于“柔性消能”理念，结合张弦梁结构和竖向预应力锚杆技术，提出一种既能改善结构受力性能、增加结构整体抗冲击能力、保证结构安全可靠，又能减小结构构件截面尺寸、节约成本、便于现场施工组装和后期运营维护的新型地锚张弦梁式泥石流格栅坝，并阐述其技术原理。根据泥石流荷载分布和新型地锚张弦梁式泥石流格栅坝的受力特征，给出其简化的内力计算方法；并利用SAP2000建立新结构有限元模型，分析了结构的整体受力，验证了构件简化计算方法的合理性；结合Python语言和Qt De? signer软件开发了相应的设计计算软件，对新型地锚张弦梁式泥石流格栅坝的内力进行求解。结果表明：提出的新结构抗冲击性能好，构件受力均匀；以后设计中应关注竖杆的剪切脆性破坏和立柱偏心受力情况，保证结构安全；变形协调仅使底层张弦梁与竖杆内力偏大，实际工程应用时，应着重验算底层构件，防止其破坏；文中提出的简化计算方法能较准确的反映结构的受力特性，具有一定的合理性，研究可为新型地锚张弦梁式泥石流格栅坝的设计计算和推广应用提供理论依据和技术支持。     

基于深度EPG的智能导航平台建设

随着三网融合的大力推进以及双向互动业务的大力开展,运营商使用原有简单的EPG不足以支撑开展更多的增值业务,不能主动为用户推荐节目,不能为运营商带来新的收入机会。作为重要的创新能力支撑系统,介绍了江苏有线智能导航平台的设计与应用,为相关广电运营商提供一定的设计参考。     

基于Word2Vec模型特征扩展的Web搜索结果聚类性能的改进

对于用户泛化和模糊的查询，将Web搜索引擎返回的列表内容聚类处理，便于用户有效查找感兴趣的内容。由于返回的列表由称为片段（snippet）的短文本组成，而传统的单词频率-逆文档频率（TF-IDF）特征选择模型不能适用于稀疏的短文本，使得聚类性能下降。一个有效的方法就是通过一个外部的知识库对短文本进行扩展。受到基于神经网络词表示方法的启发，提出了通过词嵌入技术的Word2Vec模型对短文本扩展，即采用Word2Vec模型的TopN个最相似的单词用于对片段（snippet）的扩展，扩展文档使得TF-IDF模型特征选择得到聚类性能的提高。同时考虑到通用性单词造成的噪声引入，对扩展文档的TF-IDF矩阵进行了词频权重修正。实验在两个公开数据集ODP239和SearchSnippets上完成，将所提方法和纯snippet无扩展的方法、基于Wordnet的特征扩展方法和基于Wikipedia的特征扩展方法进行了对比。实验结果表明，所提方法在聚类性能方面优于对比方法。     

基于k-shell的复杂网络最短路径近似算法

复杂网络最短路径经典算法的处理效率较低，不适用于大规模复杂网络，而现有近似算法通用性有限，且计算准确率不理想，不能满足规模日益扩大的复杂网络中的最短路径计算需求。针对于此，提出基于[k]-shell的复杂网络最短路径近似算法。算法利用节点的[k]-shell值进行网络划分并引导搜索路径，利用超点聚合处理[k]-shell子网来降低路径搜索中节点和连边的规模，通过在路径搜索过程使用双向搜索树方法提高算法的计算效率和准确率。实验结果表明，算法通用性较好，在现实与仿真大规模复杂网络中均具有较高的计算效率和准确率。     

An improved cuckoo search algorithm for the problem of electric distribution network reconfiguration

Power loss reduction has an important role in operating electric distribution network system. There are a lot of methods for reduction power loss such as capacitor placement, distributed generation placement and electric distribution network reconfiguration (EDNR). Among these methods, the EDNR is an efficient technique to reduce power loss due to without taking any costs. However, the EDNR problem is a nonlinear, discrete problem and lots of extreme points. Therefore, it is necessary to have efficient methods for solving the EDNR problem. In this paper, an improved cuckoo search algorithm (ICSA) is proposed for solving the EDNR problem. In which, based on disadvantages of exploration and exploitation process of cuckoo search algorithm (CSA) for solving the EDNR problem, a local search mechanism is added to exploit candidate solutions existing around the current best solution. The calculated results on the simple distribution networks to complex distribution networks show that ICSA has ability for finding the global optimal solution with much smaller iterations and better quality of obtained solution compared with CSA and some other improved versions of CSA. The performance comparisons with other existing methods available in previous studies and the software of Power System Simulator/Advanced Distribution Engineering Productivity Tool (PSS/ADEPT) also lead to the better electric distribution network configuration with smaller total power losses. As a result, ICSA is a potential and reliable method for solving the EDNR problems.     

基于平面不封闭图形切割的路径规划

在平面切割环节中，如何确定更短切割路径以减少加工成本、降低设备损耗和提升切割质量是工业应用和学术研究的重点。目前国内外对平面切割路径的研究主要集中于封闭图形，为此，针对在激光刀模行业中不封闭图形的问题，提出一种基于禁忌搜索的贪婪算法和贪婪准则的局部优化。首先使用构建型的贪婪算法和改进型的禁忌搜索算法相结合的方式对加工过程中的图元路径进行优化排序，随后提出贪婪准则的局部优化系数，削弱贪婪算法的“贪心”思想，解决加工路径的规划和优化问题。实验数据表明，禁忌搜索的贪婪算法和局部优化在对切割路径的规划和空行程优化上有显著效果，空行程减少50%以上，并且其优化性能和图元数量成正比，能有效地解决刀模行业以及其他激光雕刻行业中图形不封闭的切割难题。