Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.     

非常规气藏储层改造体积评价方法研究

为精确描述非常规气藏压裂后的复杂流动特征及定量评价储层改造体积（SRV），利用自主研发的缝网重构算法“破裂树生长法”建立压后缝网模型，并以此为基础提出了使用拟稳态流动时特定的压力等值线来确定SRV范围的定量评价方法，最后以长宁201井区为例进行了矿场实例分析。该方法根据微地震监测点的位置，重构出微裂缝网的连通关系。在复杂微裂缝网的基础上建立离散裂缝地质模型并进行生产数值模拟，根据数值模拟结果的压力分布精确划定SRV的范围。利用该方法计算出长宁201井区的SRV体积为0.052 1 km3，以该缝网模型的数值模拟产量预测结果符合实际生产规律，方法实用性较好。     

Predictive environmental hydrogen embrittlement on fracture toughness of commercial ferritic steels with hydrogen-modified fracture strain model

In this work, a practical numerical model with few parameters was proposed for the prediction of environmental hydrogen embrittlement. The proposed method adopts hydrogen enhanced plasticity-based mechanism in a fracture strain model to describe hydrogen embrittlement. Fracture toughness degradation of three commercial steels SA372J70, AISI4130 and X80 in high pressure hydrogen environment were investigated. Firstly, governing equations for hydrogen distribution and material damage evolution was established. Hydrogen enhanced localized flow softening effect was coupled within fracture strain dependency on stress triaxiality. Then, the numerical implementation and identification process of model parameters was described. Model parameters of the investigated steels were determined based on experiment results from literatures. Finally, with the calibrated model, fracture toughness reduction of the steels was predicted in a wide range of hydrogen pressure. The prediction results were compared with experimental results. Reasonable accuracy was reached. The proposed method is an attempt to reach balance between physical accurate prediction and engineering practicality. It is promising to provide a simplified numerical tool for the design and fit for service evaluation of hydrogen storage vessels.     

Experimental study and model predictions on helium release in an enclosure with single or multiple vents

This paper presents experiments performed at Canadian Nuclear Laboratories (CNL) to examine the dispersion behaviour of helium in a polycarbonate enclosure that was representative of a residential parking garage. The purpose was to gain a better understanding of the effect of buoyancy- or wind-driven natural ventilation on hydrogen dispersion behaviour. Although hydrogen dispersion studies have been reported extensively in the literature, gaps still exist in predictive methods for hazard analysis. Helium, a simulant for hydrogen, was injected near the centre of the floor with a flow rate ranging from 5 to 75 standard litres per minute through an upward-facing nozzle, resulting in an injection Richardson number ranging between 10^?1 and 10². The location of the nozzle varied from the bottom of the enclosure to near the ceiling to examine the impact of the nozzle elevation on the development of a stratified layer in the upper region of the enclosure. When the injection nozzle was placed at a sufficiently low elevation, the vertical helium profile always consisted of a homogenous layer at the top overlaying a stratified layer at the bottom. To simulate outdoor environmental conditions, a fan was placed in front of each vent to examine the effect of opposing or assisting wind on the dispersion. The helium transients in the uniform layer predicted with analytical models were in good agreement with the measured transients for most tests. Model improvements are required for adequately predicting transients with primarily stratified profiles or strong opposing wind.     

Removing data and using metafounders alleviates biases for all traits in Lacaune dairy sheep predictions

Bias in dairy genetic evaluations, when it exists, has to be understood and properly addressed. The origin of biases is not always clear. We analyzed 40 yr of records from the Lacaune dairy sheep breeding program to evaluate the extent of bias, assess possible corrections, and emit hypotheses on its origin. The data set included 7 traits (milk yield, fat and protein contents, somatic cell score, teat angle, udder cleft, and udder depth) with records from 600,000 to 5 million depending on the trait, ～1,900,000 animals, and ～5,900 genotyped elite artificial insemination rams. For the ～8% animals with missing sire, we fit 25 unknown parent groups. We used the linear regression method to compare “partial” and “whole” predictions of young rams before and after progeny testing, with 7 cut-off points, and we obtained estimates of their bias, (over)dispersion, and accuracy in early proofs. We tried (1) several scenarios as follows: multiple or single trait, the “official” (routine) evaluation, which is a mixture of both single and multiple trait, and “deletion” of data before 1990; and (2) several models as follows: BLUP and single-step genomic (SSG)BLUP with fixed unknown parent groups or metafounders, where, for metafounders, their relationship matrix gamma was estimated using either a model for inbreeding trend, or base allele frequencies estimated by peeling. The estimate of gamma obtained by modeling the inbreeding trend resulted in an estimated increase of inbreeding, based on markers, faster than the pedigree-based one. The estimated genetic trends were similar for most models and scenarios across all traits, but were shrunken when gamma was estimated by peeling. This was due to shrinking of the estimates of metafounders in the latter case. Across scenarios, all traits showed bias, generally as an overestimate of genetic trend for milk yield and an underestimate for the other traits. As for the slope, it showed overdispersion of estimated breeding values for all traits. Using multiple-trait models slightly reduced the overestimate of genetic trend and the overdispersion, as did including genomic information (i.e., SSGBLUP) when the gamma matrix was estimated by the model for inbreeding trend. However, only deletion of historical data before 1990 resulted in elimination of both kind of biases. The SSGBLUP resulted in more accurate early proofs than BLUP for all traits. We considered that a snowball effect of small errors in each genetic evaluation, combined with selection, may have resulted in biased evaluations. Improving statistical methods reduced some bias but not all, and a simple solution for this data set was to remove historical records.     

Liquefaction behavior of fiber-reinforced calcareous sands in unidirectional and multidirectional simple shear tests

A study on the liquefaction resistance of calcareous sands reinforced with polypropylene fibers was reported. Stress-controlled cyclic simple shear tests were conducted on specimens prepared at a relative density of 50%, with and without fiber reinforcements. The liquefaction behavior was investigated by considering the effects of fiber contents ranging from 0% to 1%, fiber lengths varying from 3 mm to 12 mm and loading patterns. The results indicated that increasing fiber content and fiber length resulted in a decrease in the deformation, a reduction in pore pressure accumulation rate, and improved the liquefaction resistance of calcareous sands. Additionally, the risk of soil liquefaction could be significantly reduced when the fiber content was greater than 0.8%. The multidirectional loading had a considerable effect in reducing the liquefaction resistance compared to unidirectional loading. Further, the stiffness degradation of calcareous sands decreased with increasing fiber content and fiber length. The pore pressure generated in the cyclic tests was analyzed and was found to be affected by fiber content. A pore pressure prediction model was proposed to obtain the pore pressure characteristics of fiber-reinforced calcareous sands under various fiber content conditions.     

A novel multi-objective optimization method: Input values effect on responses (IVER)

In this study, a novel multi-objective optimization method based on the best effect of unique input (independent variable) values on responses (dependent variables) was proposed. The proposed method was compared with optimization using Derringer & Suich function that is still the most used. The comparison was made using the response values measured in real experiments and available in the literature. The advantages of the proposed method such as not needing the polynomial model aiming to predict the response values, no parameter selection problem, being able to offer optimum range instead of single optimum value, being suitable for use with existing experimental designs and being simple and interpretable were demonstrated as a result of comparison. It was also suggested how the proposed method will be effective according to experimental designs, and application for the users' application was presented.     

带权决策表的属性约简

属性约简是粗糙集理论的重要应用。考虑将决策表中的每行都作为一条决策规则时，若把表中出现相同决策规则的次数作为权，可得到带权决策表。提出了关于带权决策表的正域约简相应的辨识矩阵并给出了证明，从而得到了约简算法。相比于决策表中的正域约简时发现，通过将决策表转化为带权决策表后，再利用算法1进行约简时，其在一定程度上优于前者。提出了近似分类精度约简相应的辨识矩阵并给出了证明。对于2个算法，在选取的UCI数据集上进行了实验验证。通过实验进一步说明了所提出算法的可行性和有效性。     

2种灰色模型在矿区地表沉陷预计中的适用性

目前矿区地表单点沉陷动态预计方法主要基于传统的水准测量数据,监测方法单一,成本高,观测点易破坏,不能保证地表形变信息的实时性,且采用灰色模型进行地表沉陷预计时只针对单一模型的应用,没有结合模型自身特点分析其适用性。以袁店二矿7221工作面为试验区域,采用合成孔径雷达差分干涉测量技术监测矿区地表沉陷量,分别建立了描述沉陷量与时间关系的GM(1,1)与灰色Verhulst模型进行地表沉陷量预计,实现了矿区地表沉陷监测与动态预计一体化。通过比较、分析GM(1,1)与灰色Verhulst模型对地表沉陷量的拟合及预计结果,得出了2种灰色模型在矿区地表沉陷预计中的适用性:在矿区开采沉陷开始至活跃前期,若地表单点沉陷量曲线呈近似单峰型,则宜采用GM(1,1)进行短期预计;当矿区地表沉陷进入衰退阶段,单点沉陷量曲线呈平底饱和状态,则宜采用灰色Verhulst模型进行中长期预计。     

四川盆地龙女寺构造龙王庙组储层特征及地震响应

2005年威远构造威寒1井龙王庙组获11×10⁴ m³/d的测试产量揭示了四川盆地内部龙王庙组勘探的突破。随着勘探的深入，川中磨溪—高石梯地区多口百万立方米气井的获得证实了龙王庙组巨大的勘探潜力。然而，龙女寺构造龙王庙组储层发育情况展现出与磨溪—高石梯（高磨主体）地区较大的差异，以传统“亮点”反射模式作为储层预测的指导思想已经无法满足现今勘探的需要。以龙女寺构造龙王庙组储层为例，借助已有岩心、薄片、测录井及地震资料，对区内龙王庙组储层与高磨主体地区龙王庙组储层进行对比研究，同时对储层的地震响应进行进一步的探索。研究表明：研究区龙王庙组发育局限台地沉积，颗粒滩相作为储层发育的最有利相带，最主要的储集岩类为颗粒云岩及晶粒云岩，储集空间包括粒间（溶）孔、晶间（溶）孔、溶洞等；研究区内储层表现出低孔低渗的特征，非均质性强，纵向展布差异大，横向可对比性差。对比分析“亮点”反射模式，采用波形聚类属性对储层进行平面分布预测，明确不同储层发育情况对应的波形特征。I类波形对应于储层发育于顶部，储层厚度>30 m；II类波形对应于储层发育于中部，储层厚度>20 m，或顶部中部发育2套相距20 m左右、厚度15 m左右的储层；I、II类波形为储层发育有利波形；III类波形对应储层较薄（<5 m）且储层呈薄互层状发育或储层欠发育；IV类波形对应储层欠发育；III、IV类波形为储层发育不利波形。该方法可有效地规避“假亮点”反射，预测结果与沉积相发育特征及实钻井储层发育情况吻合率高。