Carbon efficiency evaluation method for urban energy system with multiple energy complementary

Urban energy systems(UESs)play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization.In the context of the construction and operation strategy of UESs with multiple complementary energy resources,a comprehensive assessment of the energy efficiency is of paramount importance.First,a multi-dimensional evaluation system with four primary indexes of energy utilization,environmental protection,system operation,and economic efficiency and 21 secondary indexes is constructed to comprehensively portray the UES.Considering that the evaluation system may contain a large number of indexes and that there is overlapping information among them,an energy efficiency evaluation method based on data processing,dimensionality reduction,integration of combined weights,and gray correlation analysis is proposed.This method can effectively reduce the number of calculations and improve the accuracy of energy efficiency assessments.Third,a demonstration project for a UES in China is presented.The energy efficiency of each scenario is assessed using six operational scenarios.The results show that Scenario 5,in which parks operate independently and investors build shared energy-storage equipment,has the best results and is best suited for green and low-carbon development.The results of the comparative assessment methods show that the proposed method provides a good energy efficiency assessment.This study provides a reference for the optimal planning,construction,and operation of UESs with multiple energy sources.

CHARACTERIZATION OF EFFICIENT SOLUTIONS FOR MULTI-OBJECTIVE OPTIMIZATION PROBLEMS INVOLVING SEMI-STRONG AND GENERALIZED SEMI-STRONG E-CONVEXITY

The authors of this article are interested in characterization of efficient solutions for special classes of problems. These classes consider semi-strong E-convexity of involved functions. Sufficient and necessary conditions for a feasible solution to be an efficient or properly efficient solution are obtained.

Generating Efficient Solutions in Bilevel Multi-Objective Programming Problems

In this paper, we address bilevel multi-objective programming problems (BMPP) in which the decision maker at each level has multiple objective functions conflicting with each other. Given a BMPP, we show how to construct two artificial multiobjective programming problems such that any point that is efficient for both the two problems is an efficient solution of the BMPP. Some necessary and sufficient conditions for which the obtained result is applicable are provided. A complete procedure of the implementation of an algorithm for generating efficient solutions for the linear case of BMPP is presented. A numerical example is provided to illustrate how the algorithm operates.

Performances of different efficiency calibration methods of high-purity-germanium gamma-ray spectrometry in an inter-comparison exercise

This study reports the performances of efficiency calibrations for high-purity-germanium gamma-ray spectrometry using the source-, Laboratory Sourceless Object Calibration Software(LabSOCS)-and ANGLE-based methods in an inter-comparison exercise. Although the results of LabSOCS and ANGLE for ^(241)Am emitting lowenergy gamma rays were not very satisfactory, all of the three efficiency calibration methods passed acceptance criteria. The results confirmed the reliability of the calculation codes ANGLE and LabSOCS as alternative efficiency calibration methods in high-purity-germanium gamma spectrometry. This study is likely to promote the further application of the ANGLE and LabSOCS calculation codes in radioactivity measurements.

Well production optimization using streamline features-based objective function and Bayesian adaptive direct search algorithm

Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.This method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization efficiency.To improve optimization efficiency,a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization(BADS)algorithm is established.This new objective function,which represents the water flooding potential,is extracted from streamline features.It only needs to call the streamline simulator to run one time step,instead of calling the simulator to calculate the target value at the end of development,which greatly reduces the running time of the simulator.Then the well production optimization model is established and solved by the BADS algorithm.The feasibility of the new objective function and the efficiency of this optimization method are verified by three examples.Results demonstrate that the new objective function is positively correlated with the cumulative oil production.And the BADS algorithm is superior to other common algorithms in convergence speed,solution stability and optimization accuracy.Besides,this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional methods.It can provide a more effective basis for determining the optimal well production for actual oilfield development.

Efficiency and Size Optimization of a General Solid Oxide Fuel Cell System

An irreversible model of high temperature solid oxide fuel cells( SOFCs) working at steady-state is developed,devoted to performing the optimization with regard to two objectives:minimization of the fuel cell size and maximization of the system efficiency. The performance characteristics of the system are analyzed in details, illustrated by the curves of power density,efficiency and voltage. Genetic algorithm is used to perform the multi-objective optimization with four decision variables: the operating pressure, the fuel stoichiometric ratio, the air stoichiometric ratio and the current density. A Pareto set giving a quantative description of the trade-off between the two objectives is used to analyze the results. Optimization results prove the existence of optimal designs region for a 50 kW system with efficiency from 43% corresponding to a 14. 6 m2 electrolyte area to 48% corresponding to a 25.4 m2 electrolyte area. The SOFC model used is general and the optimization results could be applied to the practical SOFC design.

Efficiency and Feasibility of an Integrated Algorithm for Distributed Hydrological M odel Calibration

Increasing complexity of distributed hydrological model （DHM） has lowered the efficiency of convergence.In this study,global sensitivity analysis （SA） was introduced by combining multiobjective （MO） optimization for DHM calibration.Latin Hypercube-once at a time （LH-OAT） was adopted in global parameter SA to obtain relative sensitivity of model parameter,which can be categorized into different sensitivity levels.Two comparative study cases were conducted to present the efficiency and feasibility by combining SA with MO（SA-MO）.WetSpa model with non-dominated sorting genetic algorithm-Ⅱ （NSGA-Ⅱ） algorithm and EasyDHM model with multi-objective sequential complex evolutionary metropolis-uncertainty analysis （MOSCEM-UA）algorithm were adopted to demonstrate the general feasibility of combining SA in optimization.Results showed that the LH-OAT was globally effective in selecting high sensitivity parameters.It proves that using parameter from high sensitivity groups results in higher convergence efficiency.Study case Ⅰ showed a better Pareto front distribution and convergence compared with model calibration without SA.Study case Ⅱ indicated a more efficient convergence of parameters in sequential evolution of MOSCEM-UA under the same iteration.It indicates that SA-MO is feasible and efficient for high dimensional DHM calibration.

An Objective Penalty Functions Algorithm for Multiobjective Optimization Problem

By using the penalty function method with objective parameters, the paper presents an interactive algorithm to solve the inequality constrained multi-objective programming (MP). The MP is transformed into a single objective optimal problem (SOOP) with inequality constrains;and it is proved that, under some conditions, an optimal solution to SOOP is a Pareto efficient solution to MP. Then, an interactive algorithm of MP is designed accordingly. Numerical examples show that the algorithm can find a satisfactory solution to MP with objective weight value adjusted by decision maker.

Empirically Validated Software Efficiency Estimation Model: Product Operation Perspective

The quality element of a design class is important as it has a substantial listed influence on overall required quality of the software. The complexity and lengthy codes of program severely affect several quality measures, especially efficiency of the final delivered software. This paper does an appropriate review on efficiency of object oriented software, and suggests some relevant information about class design level efficiency. Program efficiency is an important factor to software quality. Moreover, if software efficiency analysis has been done in the early steps of the software creation process then it assures as a criterion to software quality. This article proposes a comprehensive research idea for estimation of the efficiency index. Subsequently, it does an extremely methodical review on design efficiency of software. After that, a design metric based efficiency estimation model at the design time has been proposed by creating the link between design properties of the program and efficiency criteria. Furthermore, the correlation is mapped among all with the help of statistical values for selected design properties and efficiency criteria. In addition, efficiency estimation model is empirically validated with try-out data.

OPTIMALITY CONDITIONS AND DUALITY RESULTS FOR NONSMOOTH VECTOR OPTIMIZATION PROBLEMS WITH THE MULTIPLE INTERVAL-VALUED OBJECTIVE FUNCTION

In this paper, both Fritz John and Karush-Kuhn-Tucker necessary optimality conditions are established for a （weakly） LU-efficient solution in the considered nonsmooth multiobjective programming problem with the multiple interval-objective function. Further, the sufficient optimality conditions for a （weakly） LU-efficient solution and several duality results in Mond-Weir sense are proved under assumptions that the functions constituting the considered nondifferentiable multiobjective programming problem with the multiple interval- objective function are convex.

METHOD OF CENTERS ALGORITHM FORMULTI-OBJECTIVE PROGRAMMING PROBLEMS

In this paper, we consider a method of centers for solving multi-objective programming problems, where the objective functions involved are concave functions and the set of feasible points is convex. The algorithm is defined so that the sub-problems that must be solved during its execution may be solved by finite-step procedures. Conditions are given under which the algorithm generates sequences of feasible points and constraint multiplier vectors that have accumulation points satisfying the KKT conditions. Finally, we establish convergence of the proposed method of centers algorithm for solving multiobjective programming problems.

Roughly <i>B</i>-invex Multi-Objective Programming Problems

In this paper, we shall be interested in characterization of efficient solutions for special classes of problems. These classes consider roughly B-invexity of involved functions. Sufficient and necessary conditions for a feasible solution to be an efficient or properly efficient solution are obtained.

A Penalty Function Algorithm with Objective Parameters and Constraint Penalty Parameter for Multi-Objective Programming

In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty function with objective parameters and constraint penalty parameter for MP and the corresponding unconstraint penalty optimization problem (UPOP) is defined. Under some conditions, a Pareto efficient solution (or a weakly-efficient solution) to UPOP is proved to be a Pareto efficient solution (or a weakly-efficient solution) to MP. The penalty function is proved to be exact under a stable condition. Then, we design an algorithm to solve MP and prove its convergence. Finally, numerical examples show that the algorithm may help decision makers to find a satisfactory solution to MP.

Open-Access Framework for Efficient Object-Oriented Development of Video Analysis Software

The increasing use of digital video everyday in a multitude of electronic devices, including mobile phones, tablets and laptops, poses the need for quick development of cross-platform video software. However current approaches to this direction usually require a long learning curve, and their development lacks standardization. This results in software components that are difficult to reuse, and hard to maintain or extend. In order to overcome such issues, we propose a novel object-oriented framework for efficient development of software systems for video analysis. It consists of a set of four abstract components, suitable for the implementation of independent plug-in modules for video acquisition, preprocessing, analysis and output handling. The extensibility of each module can be facilitated by sub-modules specifying additional functionalities. This architecture enables quick responses to changes and re-configurability;thus conforming to the requirements of agile software development practices. Considering the need for platform independency, the proposed Java Video Analysis (JVA) framework is implemented in Java. It is publicly available through the web as open-access software, supported by a growing collection of implemented modules. Its efficiency is empirically validated for the development of a representative video analysis system.

Optimality for Multi-Objective Programming Involving Arcwise Connected d-Type-I Functions

This paper deals with the optimality conditions and dual theory of multi-objective programming problems involving generalized convexity. New classes of generalized type-I functions are introduced for arcwise connected functions, and examples are given to show the existence of these functions. By utilizing the new concepts, several sufficient optimality conditions and Mond-Weir type duality results are proposed for non-differentiable multi-objective programming problem.

协调公平与效率的“四水四定”研究Ⅰ:方法与模型

针对水资源刚性约束落地缺抓手的问题,按照以水定发展、协调定规模的理念,提出“四水四定”的分析思路和控制指标,厘清各类发展目标与水资源利用的协调关系。以公平为社会目标,以效益为经济目标,提出“尊重现状、保障刚需、效率驱动、区域均衡”的协调优化准则,建立目标函数和约束条件,构建“四水四定”多目标协调模型,以满足保障刚性需求基础上的水量高效流转,确定发展规模和水量分配方案。模型选取人均GDP最大实现效率驱动,使有限水量产生更大效益;选取区域人均GDP差异最小、发展匹配度最高实现发展公平,缩小区域经济差异;通过约束条件反映水资源约束、刚性需求保障、水源用户配置关系、经济社会发展合理范围等要求;设置罚函数协调约束条件不能满足时的目标值调整。通过归一化方法将多目标转化为单目标,基于现状设置初始条件,采用线性规划等方法求解,得出协调产业发展和水量优化分配的整体结果,通过结果评价反馈调整,形成可服务于经济社会发展和水资源管控决策的方案。

基于改进YOLOv8的煤矿输送带异物检测

现有基于深度学习的输送带异物检测模型较大,难以在边缘设备部署,且对不同尺寸异物和小目标异物存在错检、漏检情况。针对上述问题,提出一种基于改进YOLOv8的煤矿输送带异物检测方法。采用深度可分离卷积、压缩和激励(SE)网络将YOLOv8主干网络中C2f模块的Bottleneck重新构建为DSBlock,在保持模型轻量化的同时提升检测性能;为增强对不同尺寸目标物体信息的获取能力,引入高效通道注意力(ECA)机制,并对ECA的输入层进行自适应平均池化和自适应最大池化操作,得到跨通道交互MECA模块,以增强模块的全局视觉信息,进一步提升异物识别精度;将YOLOv8的3个检测头修改为4个轻量化小目标检测头,以增强对小目标的敏感性,有效降低小目标异物的漏检率和错检率。实验结果表明:改进YOLOv8的精确度达91.69%,mAP@50达92.27%,较YOLOv8分别提升了3.09%和4.07%;改进YOLOv8的检测速度达73.92帧/s,可充分满足煤矿输送带异物实时检测的需求;改进YOLOv8的精确度、mAP@50、参数量、权重大小和每秒浮点运算数均优于SSD,Faster-RCNN,YOLOv5,YOLOv7-tiny等主流目标检测算法。

考虑需求响应和热能梯级利用的园区综合能源系统多目标优化调度

园区综合能源系统(Park-level Integrated Energy System,PIES)供能设备多样,能源耦合机制复杂,是典型的复杂能源系统。为实现PIES低碳经济运行并提升风电消纳量以及解决系统因用能结构不合理导致的能源利用效率偏低问题,文中建立了电热需求响应模型优化负荷,并充分考量能量的“质”与“量”,基于热力学第一、第二定律建立了对系统碳排放约束性较强的综合能效模型,并将系统的热负荷根据能源品位进行细化区分,依据热能梯级利用理论,建立了能量耦合设备的数学模型。最后结合系统经济成本目标及系统综合能效目标建立了园区综合能源系统多目标优化调度模型,实现针对系统内各设备出力的调度。算例分析表明,文中提出的优化调度方案能够在提升系统风电消纳率及运行经济性的同时兼顾系统的低碳高效运行。

二层多目标随机规划逼近弱有效解集的上半收敛性

为研究二层多目标随机规划逼近问题的弱有效解与精确的弱有效解之间的逼近收敛性,针对上、下层都带有约束条件的一类多目标二层随机规划的逼近问题,构建了二层多目标随机规划逼近问题的弱有效解集的上半收敛性理论框架。即在假设下层反馈到上层的最优解集函数为凸函数的前提下,借助严格凸函数的性质,利用多目标随机规划的弱有效解可以表示成相应的单目标随机规划最优解集交集的结构特征,建立了二层多目标随机规划逼近弱有效解集的上半收敛性,提供了逼近方法求解二层多目标随机规划弱有效解集可以近似替代精确的弱有效解集的理论依据。

以四重目标理论为指导同质化管理急诊跨科收治患者的效果评价

目的以四重目标理论为指导实施急诊患者跨科收治同质化护理管理并进行应用效果评价。方法法成立研究小组,开展急诊跨科同质化管理培训及管理。选取2022年1月一6月于杭州市某三级甲等医院急诊跨科收治的患者为试验组(n=915),2021年7月一12月常规护理患者为对照组(n=917),比较两组的护理质量安全指标(全院急救紧急呼叫系统启动、快速反应小组启动、给药错误、坠床跌倒、压力性损伤例数)以及效率指标(首次开具医属时间、平均住院日、患者和医生对护士的满意度)。结果与对照组相比,试验组紧急呼叫系统启动率、快速反应小组启动率、给药错误、坠床跌倒、压力性损伤例数均下降;首次开具医瞩时间缩短(P<0.001);相近病种平均住院日显著下降(P=0.003);患者及医生对护士满意度均显著增高(P<0.001)。结论应用四重目标关键因素建立的急诊患者跨科收治同质化护理管方法,有助于改善护士对患者的安全管理及效率管理,同时提高急诊跨科患者及主管医生对护士的满意度。