基于D-optimal法优化香菇菌种培养基质配方的研究

为了筛选和优化香菇原种及栽培种的培养基质配方,采用D-optimal设计方法,以麦粒和木屑不同配比为原料优化香菇原种培养基质,以木屑、玉米芯、麸皮不同配比为原料优化香菇栽培种培养基质,以香菇品种L808作为供试菌种,分别以其菌丝萌发期、菌丝长速、满袋期为评价指标,通过对各评价指标的测量,建立了各配比基质与香菇培养基质配方响应值之间的回归模型,从而科学的优化出香菇原种及栽培种栽培基质的配方。试验结果表明,香菇原种栽培基质最优配方为50%麦粒+50%木屑;香菇栽培种栽培基质最优配方为37.69%玉米芯+23.33%麸皮+38.98%木屑。在以上2个配方的栽培基质接种后,香菇菌丝的生长旺盛,萌发期短、满袋期短,且理化性质较优,说明优化得到的栽培基质配方具有较高的可行性,该设计方法也在优化培养料配比上是科学并且可行的。

TDOA and track optimization of UAV swarm based on D-optimality

To solve the problem of time difference of arrival(TDOA)positioning and tracking of targets by the unmanned aerial vehicles(UAV)swarm in future air combat,this paper adopts the TDOA positioning method and uses time difference sensors of the UAV swarm to locate target radiation sources.Firstly,a TDOA model for the target is set up for the UAV swarm under the condition that the error variance varies with the received signal-to-noise ratio.The accuracy of the positioning error is analyzed by geometric dilution of precision(GDOP).The D-optimality criterion of the positioning model is theoretically derived.The target is positioned and settled,and the maximum value of the Fisher information matrix determinant is used as the optimization objective function to optimize the track of the UAV in real time.Simulation results show that the track optimization improves the positioning accuracy and stability of the UAV swarm to the target.

Optimization of mechanical properties using D-optimal factorial design of experiment: Electromagnetic stir casting process of A357-SiC nanocomposite

Electromagnetic stir casting process of A357-Si C nanocomposite was discussed using the D-optimal design of experiment(DODOE) method. As the main objective, nine random experiments obtained by DX-7 software were performed. By this method, A357-Si C nanocomposites with 0.5, 1.0 and 1.5 wt.% Si C were fabricated at three different frequencies(10, 35 and 60 Hz) in the experimental stage. The microstructural evolution was characterized by scanning electron and optical microscopes, and the mechanical properties were investigated using hardness and roomtemperature uniaxial tensile tests. The results showed that the homogeneous distribution of Si C nanoparticles leads to the microstructure evolution from dendritic to non-dendritic form and a reduction of size by 73.9%. Additionally, based on DODOE, F-values of 44.80 and 179.64 were achieved for yield stress(YS) and ultimate tensile strength(UTS), respectively, implying that the model is significant and the variables(Si C fraction and stirring frequency) were appropriately selected. The optimum values of the Si C fraction and stirring frequency were found to be 1.5 wt.% and 60 Hz, respectively. In this case, YS and UTS for A357-Si C nanocomposites were obtained to be 120 and 188 MPa(57.7% and 57.9 % increase compared with those of the as-cast sample), respectively.

基于D-optimality准则的多输入多输出雷达阵列设计

为了最小化参数估计的均方误差,提出了基于D-optimality准则(DOBC)的多输入多输出雷达天线几何设计方法。严格推导了天线几何在DOBC准则下需要满足的约束条件;进行了敏感性分析,DOBC准则下的天线几何只与目标方位角之差有关,而与具体的方位角值无关;并推导了远场条件下参数估计的克拉美罗界(CRLB),DOBC准则可以看成一种修正的CRLB,其为最大似然估计算法提供了更严格的下界约束。仿真结果表明,与最小冗余阵列、均匀阵列相比,DOBC准则下的天线几何具有更优越的参数估计性能,且其不受阵列孔径的约束,可以通过扩大孔径,进一步提高分辨力。但随着孔径的提高,方向图的伪峰值会升高,在低信噪比条件下,会造成很大的参数估计误差,因此需要根据实际应用需求,选择合适的孔径大小。

Optimization of Proportion and Formulation Process of Jinweng Granule by D-Optimal Mixture Design

[Objectives] To study the optimal proportion and formulation process of Jinweng granule,the physicochemical properties of the optimal preparing process was observed. [Methods] Adopting the D-optimal mixture design method,selecting the mixing ratio of starch,dextrin,fumei powder and lactose as tested factors,and selecting the most significant factor between hygroscopicity,formability,solubility as the evaluation index,the optimal proportion of filler was examined by system experiments. Granularity,solubility,the angle of repose,and critical relative humidity( CRH) were used to evaluate the optimal proportion and formulation process of Jinweng granule. [Results]The optimal prescription of Jinweng granule is extract∶ starch∶ dextrin∶ lactose∶ fumei powder( 1∶ 0. 5∶ 0. 05∶ 0. 3∶ 0. 15),and the binder was consisted of 1% sodium carboxymethylcellulose( CMC) slurry and 3% starch syrup. The CRH of the optimum formulation process of granule is 72%,and the fluidity,solubility and granularity were qualified. [Conclusions] The process model established by D-optimum mixture design has good predictability,and the granule prepared by the optimal proportion has good repeatability,and the granule proportion and formulation process is stable and reliable.

Application of D-Optimal Study Design with Contour Surface Response for Designing Sustained Release Gliclazide Matrix Tablets

An optimized formulation of a sustained release tablet of Gliclazide was developed. The use of Doptimal design with a polynomial statistical model to analyze dissolution data reduced the number of laboratory tests required to obtain an optimal dosage form. The final formulation contained 22 mg of Methocel&regE15LV, 16.5 mg Methocel&regE15 and 10.0 mg of Dibasic Calcium Phosphate per 30 mg Gliclazide sustained release tablet. Dissolution studies performed on tablets from 5000 tablet test batches released greater than 90 percent of loaded drug in eight hours. Drug release from the optimized tablets followed a pattern more closely similar to zero-order than other mechanisms of drug release tested. Storage of tablets in accelerated and ambient conditions for 6 and 12 months respectively did not alter any of the physico-chemical properties, drug release or the drug release rate compared to initial observations and dissolution data of the prepared tablets. The addition of potassium phosphate and monosodium phosphate to the tablet reduced the effect pH has on Gliclazide dissolution compared to the commercially available product.

基于D-optimal试验设计的公共交通出行logit模型

以成都到龙泉片区的交通通道为研究对象,假设通道开通地铁的情况下,采用D-optimal试验设计意愿调查问卷,选择费用、时间等变量以及个人属性作为效用变量,建立公共交通出行的多项logit模型,结合意愿调查数据对模型进行求解,分析通道中公共交通出行选择行为,并预测成都到龙泉片区主要交通方式的客流分担率。分析表明,地铁将承担通道中大部分的客流。

A New D-optimal Design Scheme for the Identification of Cubic Polynomials

In this paper, the limitations of the single cube D-optimal design scheme is studied, and a double cube D-optimal design scheme is suggested in order to overcome the limitations. For a sort of incomplete cubic polynomials, the test design of the identification is developed with this new scheme, and the comparation with the single cube scheme is also given. This scheme is shown to be perfectly suitable for the optimal identification of the complete cubic polynomials.

The Construction of Locally D-Optimal Designs by Canonical Forms to an Extension for the Logistic Model

Logistic regression models for binary response problems are present in a wide variety of industrial, biological, social and medical experiments;therefore, optimum designs are a valuable tool for experimenters, leading to estimators of parameters with minimum variance. Our interest in this contribution is to provide explicit formulae for the D-optimal designs as a function of the unknown parameters for the logistic model where q is an indicator variable. We have considered an experiment based on the dose-response to a fly insecticide in which males and females respond in different ways, proposed in Atkinson et al. (1995) [1]. To find the D-optimal designs, this problem has been reduced to a canonical form.

Formulation Optimization Utilizing D-Optimal Experimental Design of Oral Capsules Containing Enteric-Coated Pellets of Lansoprazole and<i>in vivo </i>Bioequivalence

An optimized formulation of capsules containing Lansoprazole enteric-coated pellets using D-Optimal design with a polynomial statistical model were prepared by using Eudragit?L100 as an enteric coated polymer to provide resistance to simulated gastric acid dissolution in buffer media. D-Optimal experimental design was used to determine the optimal level for three coating layers that were applied to formulate the enteric-coated pellets including a drug loading layer, a sub-coating, and an outer enteric coating. Dissolution studies were performed on the prepared Lansoprazole capsules. Less than 5 percent of Lansoprazole was released in 60 minutes in an acidic dissolution medium (pH 1.2) and greater than 90 percent of active ingredient was released in the next 60 minutes in a buffer dissolution medium (pH 6.8). The Lansoprazole capsules were stable with no observable change in physico-chemical properties in accelerated and normal storage conditions for 6 and 18 months, respectively. The pharmacokinetic parameters Cmax, Tmax, AUC0-t, and AUC0-∞ were determined after administration of the D-Optimal design optimized capsules of LPZ to healthy beagle dogs and were statistically compared to Gastevin? capsules as a reference (KRKA, Slovenia) using the non-compartmental method with the aid of WinNonlin 5.2 software. The analysis of variance showed that the two formulations did not demonstrate bioequivalence using a 90% confidence interval range (80% - 120%) of Cmax, AUC0-t, and AUC0-∞. No significant difference in Tmax was found at the 0.95 significance level using the Wilcoxon signed-rank test. D-Optimal Experimental Design provided definitive direction for an optimal formulation of capsules containing enteric-coated pellets of lansoprazole loaded within the coating of pellets that provided similar bioequivalence to Gastevin.

D-optimal Designs for Multiresponse Linear Models with a Qualitative Factor Under General Covariance Structure

This paper considers a linear regression model involving both quantitative and qualitative factors and an m-dimensional response variable y. The main purpose of this paper is to investigate D-optimal designs when the levels of the qualitative factors interact with the levels of the quantitative factors. Under a general covariance structure of the response vector y, here we establish that the determinant of the information matrix of a product design can be separated into two parts corresponding to the two marginal designs. Moreover, it is also proved that D-optimal designs do not depend on the covariance structure if we assume hierarchically ordered system of regression models.

D-Optimal Designs for Hierarchical Linear Models with Heteroscedastic Errors

This paper investigates the optimal design problem for the prediction of the individual parameters in hierarchical linear models with heteroscedastic errors.An equivalence theorem is established to characterize D-optimality of designs for the prediction based on the mean squared error matrix.The admissibility of designs is also considered and a sufficient condition to simplify the design problem is obtained.The results obtained are illustrated in terms of a simple linear model with random slope and heteroscedastic errors.

NOTE ON REGULAR D-OPTIMAL MATRICES

Let A be a j x d (0,1) matrix. It is known that if j = 2k - 1 is odd, then det(AAT) ≤ (j+1)((j+1)d/4j)j; if j is even, then det(AAT) ≤ (j+1)((j+2)d/4(j+1))j. A is called a regular D-optimal matrix if it satisfies the equality of the above bounds. In this note, it is proved that if j = 2k - 1 is odd, then A is a regular D-optimal matrix if and only if A is the adjacent matrix of a (2k - 1, k, (j + l)d/4j)-BIBD; if j = 2k is even, then A is a regular D-optimal matrix if and only if A can be obtained from the adjacent matrix B of a (2k + 1,k + 1,(j + 2)d/4(j +1))-BIBD by deleting any one row from B. Three 21 x 42 regular D-optimal matrices, which were unknown in [11], are also provided.

D-optimal population designs in linear mixed effects models for multiple longitudinal data

The main purpose of this paper is to investigate D-optimal population designs in multi-response linear mixed models for longitudinal data.Observations of each response variable within subjects are assumed to have a first-order autoregressive structure,possibly with observation error.The equivalence theorems are provided to characterise theD-optimal population designs for the estimation of fixed effects in the model.The semi-Bayesian D-optimal design which is robust against the serial correlation coefficient is also considered.Simulation studies show that the correlation between multi-response variables has tiny effects on the optimal design,while the experimental costs are important factors in the optimal designs.

考虑个体异质性的大型活动参与意向选择行为

为研究个体异质性对于大型活动参与意向选择的影响,构建了基于潜在类别选择模型的大型活动参与意向选择模型。使用D-optimal设计法生成了大型活动参与意向调查中的选择情景,并假设以天津市奥体中心为大型活动举办地,对天津市居民开展了大型活动参与意向调查。根据调查获取的数据,使用EM算法对模型进行了参数估计。模型结果表明:天气、活动时间、票价、活动类型、政策复杂度等是影响大型活动参与意向选择的主要因素。模型将潜在的大型活动参与者划分为天气敏感型群体、活动时间敏感型群体、票价敏感型群体3类,分别占样本总体的30%、15%、55%,区分度为0.81,其中类别1对天气类型最为敏感,对活动举办时间和票价不敏感;类别2对活动举办时间最为敏感,对天气的敏感程度较低;类别3对票价最为敏感,对活动时间和政策复杂度不敏感。

固废基复合胶凝材料配比优化设计及协同效应研究

利用多种固废协同制备固废基复合胶凝材料(MSSWB)是固废资源化利用的有效途径,然而,相对复杂的原材料组成和较低的力学性能限制了MSSWB的应用。本文首先借助D-optimal设计方法设计了100组实验配比作为数据集,然后创建了PSO-BP模型用于MSSWB力学性能的预测,并通过粒子群优化算法(PSO)确定了各原材料的最佳质量配比,最后采用XRD、TG-DTG和NMR等微观分析方法研究了MSSWB的水化产物以及多元固废之间的协同效应。结果表明:PSO-BP模型可有效预测胶凝材料的抗压强度,经粒子群优化算法优化后的配比强度明显高于未优化配比强度,最优配比组的28 d胶砂抗压强度较未优化配比组提高了20.8%;优化配比组的较高强度主要与水化产物钙矾石和C-S-H凝胶生成量较多且水化产物之间的交联度较高有关,这表明各原材料配比优化之后,其协同效应更加明显。

固废基充填胶凝材料配比分步优化及其水化胶结机理

充填体强度对安全高效采矿至关重要,而胶凝材料是获得高强度充填体的关键.本文以工业固废为原料,首先借助D-optimal设计方法通过建立强度回归模型和因素影响分析得到矿渣激发剂最佳配比,然后通过矿渣掺量优化试验获得最佳矿渣掺量,进而获得胶凝材料完整配比;并以水泥为参照,借助X射线衍射仪和扫描电镜从水化产物和充填体微观结构揭示充填体强度形成机制.结果表明:(1)激发剂各组分对矿渣敏感顺序为:氢氧化钠﹥熟石灰﹥脱硫石膏﹥硫酸钠,且相互之间存在不同程度的交互作用;(2)在最佳质量配比(矿渣85.00%,熟石灰8.03%,硫酸钠3.96%,脱硫石膏1.85%,氢氧化钠1.16%)下,可获得超过单一水泥3.5倍的早期(1~3 d)强度和2倍的后期(7~28 d)强度;(3)高强度充填体的形成主要与水化产物钙矾石(AFt)和C–S–H有关,钙矾石在早期快速成核与生长,形成有效物理填充作用是形成较高早期强度的主要原因,后期强度则得益于不断累积的C–S–H的包裹黏结作用,使充填体结构进一步致密化.使用该固废基胶凝材料有助于矿山安全采矿;工业固废质量占比86.85%,协同解决了尾砂、矿渣、脱硫石膏等固废;D-optimal设计方法可用于激发剂等多物料混合物的配比设计和因素作用分析.

基于应变响应的结构动态载荷识别方法

提出了基于结构应变响应的动态载荷识别方法。首先,开展结构动态响应理论分析,推导结构动态响应的应变表达,构建基于应变响应的动态载荷识别模型;其次,基于D-optimal算法,对应变响应采集所涉及的贴片数量和方位进行优化计算;然后,以方形悬臂薄板和汽车拖曳臂的动态载荷识别为例,分别进行正弦和随机载荷的识别,分析识别激励的误差来源;最后,采用Pearson相关系数和拟合系数,衡量识别载荷与原始载荷的相似程度和幅值差异情况。结果表明,方形薄板识别激励与原始激励吻合较好,拖曳臂识别激励与原始信号的波形基本保持一致,但幅值有一定的差异。

大数据分位数回归下基于信息阵的最优子抽样

基于D-optimality准则构造了分位数回归中基于信息阵的最优子抽样方法.从理论角度证明了此方法相较于以往方法存在优势,即所含信息量会随总样本量的增加而增加.通过模拟实验比较了新方法和均匀子抽样、基于L-optimality准则的子抽样在不同情况下的性能.实证分析表明了新方法在实践中表现出色.

基于GT-Power DoE的柴油机进气系统多目标多参数优化

为进一步提升某船用柴油机的动力性、经济性和运行的可靠性,对柴油机的进气系统开展了多目标多参数的优化设计。基于柴油机工作过程及冷却系统耦合仿真模型,采用DoE中D-optimal抽样方法,以普通最小二乘法建立起多个变量因子的响应面模型,并采用多目标优化方法进行非归一化求解,得到额定工况下进气系统结构参数及运行参数的优化解集和最优解。仿真结果表明:优化后整机的输出功率及扭矩分别提升了3.8 kW和14.3 N·m;涡前排温、峰值缸压以及燃油消耗率分别降低了40℃,2.5 bar和2.1 g/(kW·h)。