Marginal optimization method to improve the inconsistent comparison matrix in the analytic hierarchy process

To improve the inconsistency in the analytic hierarchy process(AHP), a new method based on marginal optimization theory is proposed. During the improving process, this paper regards the reduction of consistency ratio(CR) as benefit, and the maximum modification compared to the original pairwise comparison matrix(PCM) as cost, then the improvement of consistency is transformed to a benefit/cost analysis problem. According to the maximal marginal effect principle, the elements of PCM are modified by a fixed increment(or decrement) step by step till the consistency ratio becomes acceptable, which can ensure minimum adjustment to the original PCM so that the decision makers’ judgment is preserved as much as possible. The correctness of the proposed method is proved mathematically by theorem. Firstly, the marginal benefit/cost ratio is calculated for each single element of the PCM when it has been modified by a fixed increment(or decrement).Then, modification to the element with the maximum marginal benefit/cost ratio is accepted. Next, the marginal benefit/cost ratio is calculated again upon the revised matrix, and followed by choosing the modification to the element with the maximum marginal benefit/cost ratio. The process of calculating marginal effect and choosing the best modified element is repeated for each revised matrix till acceptable consistency is reached, i.e., CR<0.1. Finally,illustrative examples show the proposed method is more effective and better in preserving the original comparison information than existing methods.

Influence of Design Margin on Operation Optimization and Control Performance of Chemical Processes

Operation optimization is an effective method to explore potential economic benefits for existing plants. The m.aximum potential benefit from operationoptimization is determined by the distances between current operating point and process constraints, which is related to the margins of design variables. Because of various ciisturbances in chemical processes, some distances must be reserved for fluctuations of process variables and the optimum operating point is not on some process constraints. Thus the benefit of steady-state optimization can not be fully achied（ed while that of dynamic optimization can be really achieved. In this study, the steady-state optimizationand dynamic optimization are used, and the potential benefit-is divided into achievable benefit for profit and unachievable benefit for control. The fluid catalytic cracking unit （FCCU） is used for case study. With the analysis on how the margins of design variables influence the economic benefit and control performance, the bottlenecks of process design are found and appropriate control structure can be selected.

Margin optimization algorithm for digital subscriber lines based on particle swarm optimization

The margin maximization problem in digital subscriber line（DSL） systems is investigated.The particle swarm optimization（PSO） theory is applied to the nonconvex margin optimization problem with the target power and rate constraints.PSO is a new evolution algorithm based on the social behavior of swarms, which can solve discontinuous, nonconvex and nonlinear problems efficiently.The proposed algorithm can converge to the global optimal solution, and numerical example demonstrates that the proposed algorithm can guarantee the fast convergence within a few iterations.

System optimization-oriented spare parts dynamic configuration model for multi-echelon multi-indenture system

In order to optimize the spares configuration project at different stages during the life cycle, the factor of time is considered to relax the assumption of the spares steady demand in multi-echelon technique for recoverable item control (METRIC) theory. According to the method of systems analysis, the dynamic palm theorem is introduced to establish the prediction model of the spares demand rate, and its main influence factors are analyzed, based on which, the spares support effectiveness evaluation index system is studied, and the system optimization-oriented spares dynamic configuration method for multi-echelon multi-indenture system is proposed. Through the analysis of the optimization algorithm, the layered marginal algorithm is designed to improve the model calculation efficiency. In a given example, the multi-stage spares configuration project during its life cycle is gotten, the research result conforms to the actual status, and it can provide a new way for the spares dynamic optimization.

Chaos quantum particle swarm optimization for reactive power optimization considering voltage stability

The reactive power optimization considering voltage stability is an effective method to improve voltage stablity margin and decrease network losses,but it is a complex combinatorial optimization problem involving nonlinear functions having multiple local minima and nonlinear and discontinuous constraints. To deal with the problem,quantum particle swarm optimization (QPSO) is firstly introduced in this paper,and according to QPSO,chaotic quantum particle swarm optimization (CQPSO) is presented,which makes use of the randomness,regularity and ergodicity of chaotic variables to improve the quantum particle swarm optimization algorithm. When the swarm is trapped in local minima,a smaller searching space chaos optimization is used to guide the swarm jumping out the local minima. So it can avoid the premature phenomenon and to trap in a local minima of QPSO. The feasibility and efficiency of the proposed algorithm are verified by the results of calculation and simulation for IEEE 14-buses and IEEE 30-buses systems.

Repairable Configuration Optimization Model under Two-Echelon Inventory

Spares inventory configuration optimization is an effective way to improve readiness and reduce life cycle cost of equipment.Through analyzing two-echelon spares support system,the METRIC model basic theory was used.An inventory configuration optimization model of two-echelon spares support system was proposed which took the spares expected shortfall as the object and made the minimum repairable parts expected shortfall instead of the maximum spares supportability as the objective function.Marginal efficiency analysis algorithm was applied to optimizing the spares configuration and generating a rational spares inventory configuration.Finally,several examples are given to verify the model.

Parameters optimization in deepwater dual-gradient drilling based on downhole separation

To ensure safe drilling with narrow pressure margins in deepwater, a new deepwater dual-gradient drilling method based on downhole separation was designed. A laboratory experiment was conducted to verify the effectiveness of downhole separation and the feasibility of realizing dual-gradient in wellbore. The calculation of dynamic wellbore pressure during drilling was conducted. Then, an optimization model for drilling parameters was established for this drilling method, including separator position, separation efficiency, injection volume fraction, density of drilling fluid, wellhead back pressure and displacement. The optimization of drilling parameters under different control parameters and different narrow safe pressure margins is analyzed by case study. The optimization results indicate that the wellbore pressure profile can be optimized to adapt to the narrow pressure margins and achieve greater drilling depth. By using the optimization model, a smaller bottom-hole pressure difference can be obtained, which can increase the rate of penetration(ROP) and protect reservoirs. The dynamic wellbore pressure has been kept within safe pressure margins during optimization process, effectively avoiding the complicated underground situations caused by improper wellbore pressure.

Optimal margin in nephnm-sparing surgery for renal cell carcinoma 4 cm or less in diameter.

Objective To investigate the optimal margin in nephron-sparing surgery (NSS) for renal cell carcinoma (RCC) 4 cm or less in diameter. Methods Eighty-two kidneys with RCC 4 cm or less in diameter resected by radical nephrectomy were prospectively studied. The kidney samples were sectioned at 3 mm interval and examined for multicentricity. On each layer of tissue sectioned, parenchyma margin of 15 mm beyond pseudocapsule was continuously sectioned and examined for completeness of pseudocapsule and extra-pseudocapsule cancer lesion. The farthest distance between extra-pseudocapsule lesion and primary tumor was measured. PCNA expression was detected in 41 patients by using standard SP immunohistochemistry technique. Results The diameter of 82 primary tumors was 3. 4 ± 0. 8 cm (range 1.5-4.0 cm).Of these,31.7% (26/82) were found without intact pseudocapsules and 17.1% (14/82) with positive cancer lesions beyond pseudocapsule. The average distance between extra-pseudocapsule cancer lesion and primary tumor

基于自适应粒子群优化的代价评估Marginalized粒子滤波

针对量测受扰动情况下粒子重要性权重的精确度量和粒子的有效采样问题,提出了一种基于自适应粒子群优化的代价评估Marginalized粒子滤波。首先,在Marginalized粒子滤波框架下,通过引入代价函数和风险函数,实现了粒子重要性权重评价过程中对最新量测信息的合理利用,以降低传统的依据重要性权重度量方式中对于噪声先验信息的依赖。其次,通过对粒子分布特征信息的提取和利用,构建了粒子极限速度设定的自适应选取策略,给出了一种自适应粒子群优化方法。在此基础上,结合粒子群优化中群体优化机理来提升采样粒子对被估计状态的逼近程度,进而改善重采样后粒子的多样性。理论分析和仿真实验验证了算法的有效性。

商品期货市场运用Optimal F研究

资金管理主要用于具有杠杆的金融工具交易中头寸的管理,是影响商品期货交易成败的重要因素。本文针对我国商品期货市场运用Optimal F资金管理方法;并对于理论的应用过程中以及实际交易中可能遇到的一些问题进行分析,努力给出可行的解决办法;而对于那些目前不易解决的问题,也指出其结症所在和对未来解决方法预期。文章重点研究保证金限制的F和收益和亏损的F。

Optimal setting and placement of FACTS devices using strength Pareto multi-objective evolutionary algorithm

This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for locating and setting of thyristor controlled series capacitor(TCSC) and static var compensator(SVC) using the multi-objective optimization approach named strength pareto multi-objective evolutionary algorithm(SPMOEA). Maximization of the static voltage stability margin(SVSM) and minimizations of real power losses(RPL) and load voltage deviation(LVD) are taken as the goals or three objective functions, when optimally locating multi-type FACTS devices. The performance and effectiveness of the proposed approach has been validated by the simulation results of the IEEE 30-bus and IEEE 118-bus test systems. The proposed approach is compared with non-dominated sorting particle swarm optimization(NSPSO) algorithm. This comparison confirms the usefulness of the multi-objective proposed technique that makes it promising for determination of combinatorial problems of FACTS devices location and setting in large scale power systems.

Stabilityanalysis of tactical missile autopilots based on vector margin

A novel stability computation approach for tactical missile autopilots is detailed. The limi- tations of traditional stability margins are exhibited. Then the vector margin is introduced and com- pared with sensitivity function to show their essential relationship. The longitudinal three-loop auto- pilot for tactical missiles is presented and used as the baseline for all the available linear autopilots. Ten linear autopilot topologies using all the measurable feedback components are given with the iden- tical closed-loop characteristic equation and time-domain step response. However, the stability of the ten autopilots differs when considering the actuator dynamics, which limits their application. Then vector margin method is adopted to compute and evaluate the stability of all available autopi- lots. The analysis and computation results show that the vector margin method could better evaluate autopilot stability.

计及电能量-备用耦合的配电网与光储充电站协调优化调度方法

针对光储充电站大规模接入给配电网带来的调控压力,提出一种计及电能量和备用耦合的配电网与光储充电站协调优化调度方法。首先,建立基于随机机会约束的光储充电站经济调度模型,得到光储充电站与配电网的电能交互方案和备用需求;随后,采用鲁棒经济调度-线性潮流方法,建立计及不确定性的配电网优化调度模型,并根据Karush-Kuhn-Tucker(KKT)条件推导得到配电节点边际电价和节点备用边际电价,通过电能量和备用价格引导光储充电站友好互动,挖掘站内储能在削峰填谷和备用调节上的潜力。最后,通过算例分析验证了所提方法的有效性。

基于ICEEMDAN-PSO-LSTM的短期风速预测

提出一种改进自适应噪声完备集合经验模态分解与粒子群优化长短时记忆神经网络模型的短期风速预测方法。采用ICEEMDAN算法对日风速数据进行分解并计算相应边际谱,以谱相关性为依据对历史数据进行筛选;运用PSO算法优化LSTM神经网络参数,对输入数据进行ICEEMDAN分解,将所获得的多个模态分量分别用PSO-LSTM进行预测,并通过将各分量预测值叠加的方法得到风速预测结果。使用所提方法对国内某风电场风速进行预测,通过比较分析验证所提方法的有效性。

不同叶顶弯曲对离心叶轮性能影响机理

面对现代发动机对离心叶轮性能需求不断提高的背景,叶顶弯曲具备有效改善离心叶轮气动特性的能力,本文通过数值模拟的方式对不同叶顶弯曲方向、弯曲形式、弯曲程度的压气机性能进行预测,基于仿真结果对不同流动状态下压气机内部流场进行分析,给出了叶顶弯曲压气机性能变化机理。结果显示:负弯叶轮有助于提升压气机峰值效率,提高压气机堵塞流量。正弯叶轮则在损失部分效率的情况下,使压气机失速裕度得到提升。弯曲叶轮主要通过改善叶顶前缘载荷,重构叶轮通道内静压分布,从而削弱激波强度、减少二次流损失、抑制低能涡发展,达到提升压气机性能的目的。本文研究结果可为离心压气机叶片改型设计提供参考。

基于变分模态分解和深度多核极限学习机的轴承故障分类

针对轴承故障分类任务中核极限学习机(kernel extreme learning machine,KELM)超参数选择困难、模型运算速度慢的问题,提出一种基于深度混合核极限学习机(deep hybrid kernel extreme learning machine,DHKELM)的轴承故障分类方法,利用天鹰优化算法(aquila optimization algorithm,AO)实现该模型超参数的优化选择。首先,以峰度指数作为鲸鱼优化算法(whale optimization algorithm,WOA)的适应度函数,对变分模态分解(variational mode decomposition,VMD)的相关参数寻优,利用最优参数组合进行VMD分解,得到k个模态分量并求其希尔伯特-黄变换(Hilbert-Huang Transform,HHT)边际谱作为特征数据,将其作为天鹰优化DHKELM分类器的输入,对不同状态的轴承故障进行识别。实验结果表明,KELM,DHKELM,天鹰优化DHKELM三种分类模型故障识别准确率分别为94%,96.67%,98.34%,运算时间分别为0.0631,0.0360,0.0175 s,证明AO-DHKELM识别准确率和运算速度均具有明显优势。

天然酯绝缘油对220 kV电力变压器主绝缘性能的影响分析

为了分析天然酯绝缘油对高压变压器绝缘性能的影响,本研究以一台220 kV电力变压器为研究对象,对其进行波过程计算得到雷电冲击全波下的节点电位与油道梯度电压,并建立变压器主绝缘电场计算模型得到工频及雷电全波电压下的电场分布,再计算绝缘裕度。结果表明:天然酯绝缘油变压器在工频下主绝缘裕度较大,而在雷电全波下该值较小。通过改进天然酯绝缘油变压器的绝缘结构,可缩小天然酯绝缘油变压器中压、高压绕组间主绝缘距离约6%,增大调压绕组匝绝缘厚度及角环半径,可使其在雷电全波下的绝缘裕度最小值提高15%,同时有效节约了成本。

具有间隔分布优化的最小二乘支持向量机

最小二乘支持向量机(Least Squares Support Vector Machine,LSSVM)通过求解一个线性等式方程组来提高支持向量机(Support Vector Machine,SVM)的运算速度。但是,LSSVM没有考虑间隔分布对于LSSVM模型的影响,导致其精度较低。为了增强LSSVM模型的泛化性能,提高其分类能力,提出一种具有间隔分布优化的最小二乘支持向量机(LSSVM with margin distribution optimization,MLSSVM)。首先,重新定义间隔均值和间隔方差,深入挖掘数据的间隔分布信息,增强模型的泛化性能;其次,引入权重线性损失,进一步优化了间隔均值,提升模型的分类精度;然后,分析目标函数,剔除冗余项,进一步优化间隔方差;最后,保留LSSVM的求解机制,保障模型的计算效率。实验表明,新提出的分类模型具有良好的泛化性能和运行时间。

考虑梅雨汛期防洪安全的水电富集型虚拟电厂优化调度

梅雨季节是中国长江中下游地区的特殊汛期,持续性降雨和突发性暴雨特性导致水电站群的调度策略尤其要兼顾流域防洪安全。为此,提出了考虑梅雨汛期防洪风险的水电富集型虚拟电厂(HEVPP)调度策略。首先,基于典型梅雨时空分布以及水电站防洪安全裕度特性,设计了考虑防洪风险偏好及降雨量不确定性的梅雨汛期库容调控方法;其次,针对HEVPP进行防洪风险的精细化建模,定义了基于剩余防洪库容理论的HEVPP防洪性能评估指标,并进一步提出了基于安全裕度的条件风险价值(CVaR)防洪风险成本计算方法;然后,以虚拟电厂经济效益最大化为目标,构建了考虑梅雨季节降雨特性及防洪风险成本的HEVPP优化调度模型;最后,通过中国浙江省丽水市某HEVPP的算例分析表明,所提调度策略能够反映流域水电站的拓扑特性,充分挖掘梅雨季节水电与风光资源间的协同调度能力,优化水电站群在不同防洪风险偏好下的蓄水策略,在保证流域防洪安全的基础上提升HEVPP的运行效益。

整级端壁造型对压气机总体性能影响的数值研究

以NASA Stage35为研究对象,通过NUMECA/Design3d商用优化软件,采用人工神经网络(ANN)与多目标遗传算法(NSGA-Ⅱ)相结合的方法,在喘振点附近对压气机转子和静子轮毂进行优化造型,对流场结构、气动性能以及压气机稳定性进行分析。结果表明:非轴对称端壁削弱了转子通道内的二次流强度,消除了静子前缘的马蹄涡,压气机的气动性能得到明显改善,压气机在不同设计转速下的喘振裕度都有增加,工作的稳定性得到提高。