基于选择稳定性优化的卷烟吸阻快速预测

卷烟吸阻是卷烟设计制造中的核心指标。因涉及影响因素多且具有复杂的非线性特性,无论是基于多孔介质流体力学模型还是基于大量工程实践的经验模型,均无法定量指导设计与生产,至今卷烟吸阻仍以实验测试数据为评价依据。针对卷烟生产过程中产生的大量检测数据及数据的复杂多源和不断更迭的特性,提出了一种利用生产历史积累数据,通过K均值聚类算法清洗数据消除样本差异,结合自适应套索方法对输入变量进行降维处理和辅助变量选择,并利用选择稳定性评估对过程进行一致性约束,在多源数据和滚动过程一致选择出与吸阻原理模型匹配的关键影响指标,并将其作为径向基函数神经网络(RBFNN,radical basis function netural network)的输入,建立吸阻的推理预测模型。经验证,预测模型的均方误差为0.004,相对误差率控制在3%以内,实现了生产场景下的吸阻快速预测。

基于卷积神经网络和稳定性选择的农作物植被光谱分析方法

光谱特征提取是遥感植被精细化识别研究的关键.现有光谱分析方法大多无法直接高效的提取特征波段用于分类,往往依赖特征选择和预处理操作,目标识别精度不高.本文整合卷积神经网络(CNN)和稳定性选择改进光谱分析方法实现统一高效的光谱分析,以玉米、大豆、豆角、葡萄、大枣、辣椒、秋葵、芥蓝、韭菜和草皮10种农作物植被叶片光谱为实验对象,构建适用于农作物分类的CNN模型,获得植被分类结果.利用稳定性选择方法可视化CNN卷积-池化过程的特征选择结果,获得表征不同植被生化参数的特征波段.结果表明:1)改进的光谱分析方法很好的适用于光谱识别,分类准确率维持在97%~100%之间;2)该方法对光谱预处理依赖性最小,对光谱识别表现出较强的鲁棒性和泛化能力;3)特征波段的可视化结果证明了改进的光谱分析方法能够精准的提取农作物植被的敏感特征波段,间接说明了CNN模型卷积池化操作能够准确地提取光谱重要特征波段用于农作物光谱分类.

稳定特征选择的多目标蚁群优化

为了提高进化算法特征选择稳定性,提出一种面向稳定特征选择的多目标蚁群优化方法。通过抽样策略集成三种特征排序法的输出作为多目标蚁群优化的稳定性指导信息,聚合特征的费舍尔分值和最大信息系数值作为多目标蚁群优化的启发式信息,以分类正确率和扩展昆彻瓦指标值作为两个优化目标,兼顾算法的分类性能与特征选择稳定性。在四个标准数据集上进行对比实验,结果表明,所提方法能够在分类性能与稳定性方面达到较好的平衡。

水稻品种与稻瘟病菌群体互作的选择作用研究

本研究采用倒苗继代接种的实验模拟方法，研究了病菌和寄主群体互作中的定向选择和稳定性选择作用，并以此为依据初步探讨了品种抗瘟性“丧失”预测方法的设想，为抗瘟性水稻品种的合理搭配利用提供科学依据，旨在维持自然界病菌群体的相对稳定，延长抗瘟品种的使用寿命，持续控制稻瘟病灾变。

基于机器学习方法的空气质量预测与影响因素识别

空气质量指数(AQI)的精准预测及影响因素识别,对空气污染防护和治理具有重要现实意义。选取北京市2014年第一季度至2022年第二季度AQI作为研究对象,探究六大污染物、五个气象因子和十四个经济变量对空气质量影响。选用DT,RF,GBDT和XGBoost模型对AQI进行预测,并使用稳定性选择方法定量分析各个变量对AQI的贡献。结果表明:四种模型方法均有良好的预测效果,其中XGBoost和RF的预测效果最优;六大污染物中PM2.5,PM10浓度和气象因素中的风速和气压对AQI影响较大;十四个经济变量对AQI的影响差异较大,其中城镇居民人均可支配收入、第三产业GDP和规模以上工业总产值等对AQI影响较大,而第一产业GDP和公路货物运输量等影响较小。

水泥窑协同处置生活垃圾的燃烧特性分析优化

针对传统方法难以分析掺烧生活垃圾后的水泥窑复杂燃烧特性的问题,引入数据挖掘技术,以国内某水泥厂为对象,采集相关参数数据,使用稳定性选择算法分析各参数对煤耗与NOx排量的影响系数,通过随机森林算法建立煤耗与NOx排量的数学模型,结合K-means聚类算法得出关键优化参数及其最优值。结果表明,该方法能够建立精确的煤耗与NOx排量模型,挖掘出节能减排的关键优化参数及其最优目标值。通过改善关键优化参数至最优值,能够大大降低煤耗与NOx排量,可指导水泥厂优化窑内燃烧特性。

股骨粗隆间骨折内固定方法的分析

目的总结分析股骨粗隆间骨折内固定方法的临床效果及影响因素。方法股骨粗隆间骨折分为稳定性骨折和不稳定性骨折,分别选用DHS和股骨近端锁定钢板,随访观察治疗效果。结果 14例患者随访6个月～2 a,骨折愈合时间10～20个月,无一例内固定失效发生,髋关节活动范围正常。结论股骨粗隆间骨折的手术治疗除了遵守骨科的一般治疗原则外,其疗效还与手术适应症的选择、骨折稳定性的判断、不同内固定物选择、规范的早期功能锻炼康复、扶拐保护至连续性骨痂出现等有关。

基于机器学习的煤矿突水预测方法

由于影响煤矿突水的因素多、相关性强,影响模型预测精度;数据收集工作量大,成本较高,如何科学地选取特征以提高模型预测准确率成为本文重点研究内容.本文首先提出采用稳定性选择方法在已知的22个影响因素中选取7个最重要的因素,之后构建随机森林、神经网络以及支持向量机3种典型机器学习分类预测模型对特征选取前后的数据进行预测分析,实验结果表明,特征选取后的预测模型非常稳定且预测准确率可达100%,同时降低了样本数据收集成本.

Application of fuzzy optimal selection of similar slopes to the evaluation of slope stability

The numerical calculation method is widely used in the evaluation of slope stability,but it cannot take the randomness and fuzziness into account that exist in rock and soil engineering objectively.The fuzzy optimization theory is thus introduced to the evaluation of slope stability by this paper and a method of fuzzy optimal selection of similar slopes is put forward to analyze slope stability.By comparing the relative membership degrees that the evaluated object sample of slope is similar to the source samples of which the stabilities are detected clearly,the source sample with the maximal relative membership degree will be chosen as the best similar one to the object sample,and the stability of the object sample can be evaluated by that of the best similar source sample.In the process many uncertain influential factors are considered and characteristics and knowledge of the source samples are obtained.The practical calculation indicates that it can achieve good results to evaluate slope stability by using this method.

A Multi-Hop Moving Zone(MMZ) Clustering Scheme Based on Cellular-V2X

A clustering scheme based on pure V2V communications has two prominent issues i.e. broadcast storm and network disconnection. The application of the fifth generation(5G) technology to vehicular networks is an optimal choice due to its wide coverage and low latency features. In this paper, a Multihop Moving Zone(MMZ) clustering scheme is proposed by combining IEEE 802.11p with the 3rd Generation Partnership Project(3GPP) 5G cellular technology. In MMZ, vehicles are clustered up-to three hops using V2V communications based on IEEE 802.11 p aiming to reduce excessive cellular hand-off cost. While the zonal heads(ZHs) i.e. cluster heads(CHs) are selected by cellular-V2X(C-V2X) on the basis of multi-metrics i.e. relative speed, distance and link life time(LLT). The main goal of MMZ is to form stable clusters achieving high packet delivery and low latency. The simulation results using ns3 show that, 5G wide range technology significantly improves the stability of MMZ in term of ZH duration and change rate. The average Data Packet Delivery Ratio(DPDR) and E2E latency are also improved as compared to the existing clustering schemes.

Investigation of low-temperature hydrothermal stability of Cu-SAPO-34 for selective catalytic reduction of NO_x with NH_3

The low‐temperature hydrothermal stabilities of Cu‐SAPO‐34samples with various Si contents and Cu loadings were systematically investigated.The NH3oxidation activities and NH3‐selective catalytic reduction(SCR)activities(mainly the low‐temperature activities)of all the Cu‐SAPO‐34catalysts declined after low‐temperature steam treatment(LTST).These results show that the texture and acid density of Cu‐SAPO‐34can be better preserved by increasing the Cu loading,although the hydrolysis of Si-O-Al bonds is inevitable.The stability of Cu ions and the stability of the SAPO framework were positively correlated at relatively low Cu loadings.However,a high Cu loading(e.g.,3.67wt%)resulted in a significant decrease in the number of isolated Cu ions.Aggregation of CuO particles also occurred during the LTST,which accounts for the decreasing NH3oxidation activities of the catalysts.Among the catalysts,Cu‐SAPO‐34with a high Si content and medium Cu content(1.37wt%)showed the lowest decrease in NH3‐SCR because its Cu2+content was well retained and its acid density was well preserved.

Adaptive controller design based on input-output signal selection for voltage source converter high voltage direct current systems to improve power system stability

An input-output signal selection based on Phillips-Heffron model of a parallel high voltage alternative current/high voltage direct current(HVAC/HVDC) power system is presented to study power system stability. It is well known that appropriate coupling of inputs-outputs signals in the multivariable HVDC-HVAC system can improve the performance of designed supplemetary controller. In this work, different analysis techniques are used to measure controllability and observability of electromechanical oscillation mode. Also inputs–outputs interactions are considered and suggestions are drawn to select the best signal pair through the system inputs-outputs. In addition, a supplementary online adaptive controller for nonlinear HVDC to damp low frequency oscillations in a weakly connected system is proposed. The results obtained using MATLAB software show that the best output-input for damping controller design is rotor speed deviation as out put and phase angle of rectifier as in put. Also response of system equipped with adaptive damping controller based on HVDC system has appropriate performance when it is faced with faults and disturbance.

Cu-SAPO-17:A novel catalyst for selective catalytic reduction of NOx

The high-temperature(HT) and low-temperature(LT) hydrothermal stabilities of molecular-sieve-based catalysts are important for the selective catalytic reduction of NOx with ammonia(NH3-SCR). In this paper, we report a catalyst, Cu2+ loading SAPO-17, synthesized using cyclohexylamine(CHA), which is commercially available and inexpensive and is utilized in NH3-SCR reduction for the first time. After systematic investigations on the optimization of Si and Cu2+ contents, it was concluded that Cu-SAPO-17-8.0%-0.22 displays favorable catalytic performance, even after being heated at 353 K for 24 h and at 973 K for 16 h. Moreover, the locations of CHAs, host–guest interaction and the Bronsted acid sites were explored by Rietveld refinement against powder X-ray diffraction data of as-made SAPO-17-8.0%. The refinement results showed that two CHAs exist within one eri cage and that the protonated CHA forms a hydrogen bond with O4, which indicates that the proton bonding with O4 will form the Bronsted acid site after the calcination.

The research and demonstration of some major geological problems of Three Gorges Project

The research process,main contents,methods and conclusions for some major engineering geological problems of the Three Gorges Project (TGP) are reviewed and introduced,including dam site selection,regional tectonic stability and seismic activity,stability of reservoir bank and reservoir-induced earthquake.Meanwhile,the above mentioned engineering geological problems are evaluated according to the preliminary test results since TGP operation and impoundment in 2003.

Study on Stability of Ion-exchange Resin Catalysts:Ⅱ. Desulfonation during Isobutylene Dimerization

The performance of ion-exchange resin catalysts during isobutene (IB) dimerization was investigated under different IB contents,temperatures and liquid-volume hourly space velocity (LHSV) using a plug flow reactor in the absence of any selectivity enhancing component.High IB content and temperature resulted in a high conversion and C12 selectivity bu low C8 selectivity.The influence of LHSV was related with the IB content:LHSV had great effect at high IB content,while the performance of ion-exchange resin changed little with LHSV if IB content was low.The effect of water on the stability of resins was also studied.Desulfonation was observed during the C4 dimerization reaction when water was added to the feed.Chlorinated resin was more stable than conventional polystyrene-based resins during the test.

自然选择

自然选择是进化生物学中最核心的概念,同时也是导致生物进化的关键因素。自然选择是指能够导致同一种群中,不同遗传性状的分布比例在下一个世代发生变化的过程。达尔文曾形象地描述说:"可以说,自然选择每天每时每刻都在瞪大眼睛搜检着世界每个角落的生物,不放过任何一点变异,哪怕是最微小的变异。在这一过程中它不断淘汰差的,保留好的;只要一有机会,它就会悄然无声、不露痕迹地发挥作用"。

TIME SERIES FORECASTING WITH MULTIPLE CANDIDATE MODELS:SELECTING OR COMBINING?

Various mathematical models have been commonly used in time series analysis and forecasting. In these processes, academic researchers and business practitioners often come up against two important problems. One is whether to select an appropriate modeling approach for prediction purposes or to combine these different individual approaches into a single forecast for the different/dissimilar modeling approaches. Another is whether to select the best candidate model for forecasting or to mix the various candidate models with different parameters into a new forecast for the same/similar modeling approaches. In this study, we propose a set of computational procedures to solve the above two issues via two judgmental criteria. Meanwhile, in view of the problems presented in the literature, a novel modeling technique is also proposed to overcome the drawbacks of existing combined forecasting methods. To verify the efficiency and reliability of the proposed procedure and modeling technique, the simulations and real data examples are conducted in this study.The results obtained reveal that the proposed procedure and modeling technique can be used as a feasible solution for time series forecasting with multiple candidate models.

Highly selective and stable hydrogenation of heavy aromatic-naphthalene over transition metal phosphides

The present study reports a highly selective and stable catalytic approach for producing tetralin, an important chemical, solvent, and H2 storage material. Transition metal phosphides （MOP, Ni2P, Co2P, and Fe2P） were prepared by wet impregnation and temperature-programmed reduction and characterized by X-ray diffraction （XRD）, energy dispersive X-ray spectroscopy （EDX）, EDX mapping, scanning electron microscopy （SEM）, transmission electron microscopy （TEM）, brunauer-emmett- teller （BET）, temperature-programmed desorption of ammonia （NH3-TPD）, and fourier transform infrared spectroscopy of pyridine （pyridine-FTIR）. Of all the transition metal phosphides MoP was formed at a lower reduction temperature, which resuited in smaller particle size that enhanced the overall surface area of the catalyst. The existence of weak, moderate, and Lewis acidic sites over MoP were responsible for its high tetralin selectivity （90%） and stability during the 100 h reaction on-stream in a fixed-bed reactor.

Pyridinium salt-based covalent organic framework with well-defined nanochannels for efficient and selective capture of aqueous^(99)TcO_(4)^(-)

Ionic covalent organic framework(COF)materials with high specific surface areas and well-defined pore structures are desired for many applications yet seldom reported.Herein,we report a cationic pyridinium salt-based COF(PS-COF-1)with a Brunauer-Emmett-Teller(BET)surface area of 2703 m^(2) g^(-1),state-ofthe-art for an ionic COF.Aided by its ordered pore structure,chemical stability,and radiation resistance,PS-COF-1 showed exceptional adsorption properties toward aqueous ReO_(4)^(-)(1262 mg g^(-1))and ^(99)TcO_(4)^(-).Its adsorption performance surpassed its corresponding amorphous analogue.Importantly,PS-COF-1 exhibited fast adsorption kinetics,high adsorption capacities,and selectivity for ^(99)TcO_(4)^(-)and ReO_(4)^(-)at high ionic strengths,leading to the successful removal of ^(99)TcO_(4)^(-)under conditions relevant to low-activity waste streams at US legacy Hanford nuclear sites.In addition,PS-COF-1 can rapidly decontaminate ReO_(4)^(-)/^(99)TcO_(4)^(-)polluted potable water(~10 ppb)to drinking water level(0 ppb,part per billion)within 10 min.Density functional theory(DFT)calculations revealed PS-COF-1 has a strong affinity for ReO_(4)^(-)and ^(99)TcO_(4)^(-),thereby favoring adsorption of these low charge density anions over other common anions(e.g.,Cl^(-),NO_(3)^(-),SO_(4)^(2-),CO_(3)^(2-)).Our work demonstrates a novel cationic COF sorbent for selective radionuclide capture and legacy nuclear waste management.

Extremely stable amidoxime functionalized covalent organic frameworks for uranium extraction from seawater with high efficiency and selectivity

Uranium extraction from seawater is of strategic significance for nuclear power generation.Amidoximebased functional adsorbents play indispensable roles in the recovery of seawater uranium with high efficiency.Nevertheless,balancing the adsorption capacity and selectivity is challenging in the presence of complicated interfering ions especially vanadium.Herein,a polyarylether-based covalent organic framework functionalized with open-chain amidoxime(COF-HHTF-AO)was synthesized with remarkable chemical stability and excellent crystallinity.Impressively,the adsorption capacity of COF-HHTF-AO towards uranium in natural seawater reached up to 5.12 mg/g,which is 1.61 times higher than that for vanadium.Detailed computational calculations revealed that the higher selectivity for uranium over vanadium originated from the specific bonding nature and coordination pattern with amidoxime.Combining enhanced adsorption capacity,excellent selectivity and ultrahigh stability,COF-HHTF-AO serves as a promising adsorbent for uranium extraction from the natural seawater.