区块链技术下企业财务管理探讨

本文旨在探讨区块链技术应用在企业财务管理的可优化性。首先,介绍区块链技术的基本概念、原理。其次,分析企业传统财务管理现存的问题。以此为基础,探讨应用区块链技术后对企业财务管理的优化,以期将区块链技术的潜在优势应用于企业财务管理中,提高企业财务管理效率。

Optimization model of GNSS/pseudolites structure design for open-pit mine positioning

A new pseudolites （PLs） structure optimization model of global navigation satellite system （GNSS）/PLs integration positioning system used in deep open-pit mine was presented. Position dilution of precision （Pdop） and reliability were selected as the optimization indicators to build a multi-objective optimization model to decide the optimum PLs location. A scheme was designed by establishing a four-dimensional model taking azimuth （a）, elevation angle （e） and epoch （t） of satellites as the input independent variables and Pdop as the dependent variable to calculate the optimum PLs location zone considering the real circumstances. And then the ultimate PLs location can be fixed by testing the curves of Pdop along time. A field collected Trimble R8 GPS data set in China University of Mining and Technology （CUMT） campus was used for the model test to show the effectiveness, and the proposed PLs optimum design scheme was used at the west open-pit mine of Fushun mining group Co., Ltd., in China, better Pdop and reliability have been achieved for the integration system. Both experiments show that the proposed scheme is excellent in designing GNSS/PLs system which is helpful for improving the performance of the positioning system and reducing the cost.

On Reliability-optimized Controller Placement for Software-Defined Networks

By decoupling control plane and data plane,Software-Defined Networking(SDN) approach simplifies network management and speeds up network innovations.These benefits have led not only to prototypes,but also real SDN deployments.For wide-area SDN deployments,multiple controllers are often required,and the placement of these controllers becomes a particularly important task in the SDN context.This paper studies the problem of placing controllers in SDNs,so as to maximize the reliability of SDN control networks.We present a novel metric,called expected percentage of control path loss,to characterize the reliability of SDN control networks.We formulate the reliability-aware control placement problem,prove its NP-hardness,and examine several placement algorithms that can solve this problem.Through extensive simulations using real topologies,we show how the number of controllers and their placement influence the reliability of SDN control networks.Besides,we also found that,through strategic controller placement,the reliability of SDN control networks can be significantly improved without introducing unacceptable switch-to-controller latencies.

Availability-based simulation and optimization modeling framework for open-pit mine truck allocation under dynamic constraints

We present a novel system productivity simulation and optimization modeling framework in which equipment availability is a variable in the expected productivity function of the system. The framework is used for allocating trucks by route according to their operating performances in a truck-shovel system of an open-pit mine, so as to maximize the overall productivity of the fleet. We implement the framework in an originally designed and specifically developed simulator-optimizer software tool. We make an application on a real open-pit mine case study taking into account the stochasticity of the equipment behavior and environment. The total system production values obtained with and without considering the equipment reliability, availability and maintainability (RAM) characteristics are compared. We show that by taking into account the truck and shovel RAM aspects, we can maximize the total production of the system and obtain specific information on the production availability and productivity of its components.

A Method for Surveying Control Network Optimization Based on Reliability Properties

Surveying control network optimization design is related to standards, such as precision, reliability, sensitivity and the cost, and these standards are related closely to each other. A new method for surveying control network simulation optimization design is proposed. This method is based on the inner reliability index of the observation values.

Improved Mixed Integer Optimization Approach for Data Rectification with Gross Error Candidates

Mixed integer linear programming （MILP） approach for simultaneous gross error detection and data reconciliation has been proved as an efficient way to adjust process data with material, energy, and other balance constrains. But the efficiency will decrease significantly when this method is applled in a large-scale problem because there are too many binary variables involved. In this article, an improved method is proposed in order to gen- erate gross error candidates with reliability factors before data rectification. Candidates are used in the MILP objec- tive function to improve the efficiency and accuracy by reducing the number of binary variables and giving accurate weights for suspected gross errors candidates. Performance of this improved method is compared and discussed by applying the algorithm in a widely used industrial example.

Obsolescence optimization of electronic and mechatronic components by considering dependability and energy consumption

Nowadays, rapid technological progress influences the dependability of equipments and also causes rapid obsolescence. The mechatronic and electronic equipment components are mostly affected by obsolescence. A new challenger unit possesses identical functionalities, but with higher performances. This work aims to find the optimal number of components which should be replaced by new-type units, under budgetary constraints. In this work, the new challenger unit is characterized by lower energy consumption and the optimization steps are based on genetic algorithm (GA). The result shows the importance of this type of replacement in order to economize energy consumption and to deal with obsolescence.

Reliability-based design optimization for flexible mechanism with particle swarm optimization and advanced extremum response surface method

To improve the computational efficiency of the reliability-based design optimization(RBDO) of flexible mechanism, particle swarm optimization-advanced extremum response surface method(PSO-AERSM) was proposed by integrating particle swarm optimization(PSO) algorithm and advanced extremum response surface method(AERSM). Firstly, the AERSM was developed and its mathematical model was established based on artificial neural network, and the PSO algorithm was investigated. And then the RBDO model of flexible mechanism was presented based on AERSM and PSO. Finally, regarding cross-sectional area as design variable, the reliability optimization of flexible mechanism was implemented subject to reliability degree and uncertainties based on the proposed approach. The optimization results show that the cross-section sizes obviously reduce by 22.96 mm^2 while keeping reliability degree. Through the comparison of methods, it is demonstrated that the AERSM holds high computational efficiency while keeping computational precision for the RBDO of flexible mechanism, and PSO algorithm minimizes the response of the objective function. The efforts of this work provide a useful sight for the reliability optimization of flexible mechanism, and enrich and develop the reliability theory as well.

Reliability analysis of earth slopes using hybrid chaotic particle swarm optimization

A numerical procedure for reliability analysis of earth slope based on advanced first-order second-moment method is presented,while soil properties and pore water pressure may be considered as random variables.The factor of safety and performance function is formulated utilizing a new approach of the Morgenstern and Price method.To evaluate the minimum reliability index defined by Hasofer and Lind and corresponding critical probabilistic slip surface,a hybrid algorithm combining chaotic particle swarm optimization and harmony search algorithm called CPSOHS is presented.The comparison of the results of the presented method,standard particle swarm optimization,and selected other methods employed in previous studies demonstrates the superior successful functioning of the new method by evaluating lower values of reliability index and factor of safety.Moreover,the presented procedure is applied for sensitivity analysis and the obtained results show the influence of soil strength parameters and probability distribution types of random variables on the reliability index of slopes.

Similarity Solutions for Generalized Variable Coefficients Zakharov-Kuznetsov Equation under Some Integrability Conditions

In this paper, the symmetry method has been carried over to the generalized variable coefficients Zakharov- Kuznetsov equation. The infinitesimal symmetries and the optimal system are deduced and from this optimal system seven basic fields are determined, and for every vector field in the optimal system the admissible forms of the coefficients are found and this also leads us to transform the given equation into partial differential equations in two variables. After using some referenced transformations the mentioned partial differential equations eventually reduce to ordinary differential equations. The search for solutions to those equations has yielded many exact solutions in most cases.

Reliability-based robust multi-obj ective optimization of a 5-DOF vehicle vibration model subjected to random road profiles

Ride and handling are two paramount factors in design and development of vehicle suspension systems. Conflicting trends in ride and handling characteristics propel engineers toward employing multi-objective optimization methods capable of providing the best trade-off designs compromising both criteria simultaneously. Although many studies have been performed on multi-objective optimization of vehicle suspension system, only a few of them have used probabilistic approaches considering effects of uncertainties in the design. However, it has been proved that optimum point obtained from deterministic optimization without taking into account the effects of uncertainties may lead to high-risk points instead of optimum ones. In this work, reliability-based robust multi-objective optimization of a 5 degree of freedom （5-DOF） vehicle suspension system is performed using method of non-dominated sorting genetic algorithm-II （NSGA-II） in conjunction with Monte Carlo simulation （MCS） to obtain best designs considering both comfort and handling. Road profile is modeled as a random function using power spectral density （PSD） which is in better accordance with reality. To accommodate the robust approach, the variance of all objective functions is also considered to be minimized. Also, to take into account the reliability criterion, a reliability-based constraint is considered in the optimization. A deterministic optimization has also been performed to compare the results with probabilistic study and some other deterministic studies in the literature. In addition, sensitivity analysis has been performed to reveal the effects of different design variables on objective functions. To introduce the best trade-off points from the obtained Pareto fronts, TOPSIS method has been employed. Results show that optimum design point obtained from probabilistic optimization in this work provides better performance while demonstrating very good reliability and robustness. However, other optimum points from deterministic optimizations violate the regarded constraints in the presence of uncertainties.

Optimization of the Purification Methods for Recovery of Recombinant Growth Hormone from Paralichthys olivaceus

This study aimed to optimize the purification of recombinant growth hormone from Paralichthys olivaceus. Recombinant flounder growth hormone （r-fGH） was expressed by Escherichia coli in form of inclusion body or as soluble protein under different inducing conditions. The inclusion body was renatured using two recovery methods, i.e., dilution and dialysis. Thereafter, the refolded protein was purified by Glutathione Sepharase 4B affinity chromatography and r-fGH was obtained by cleavage of thrombin. For soluble products, r-fGH was directly purified from the lysates by Glutathione Sepharase 4B affinity chromatography. ELISA-receptor assay demonstrated that despite its low receptor binding activity, the r-fGH purified from refolded inclusion body had a higher yield （2.605 mg L^-1） than that from soluble protein （1.964 mg L^-l）. Of the tested recovery methods, addition of renaturing buffer （pH 8.5） into denatured inclusion body yielded the best recovery rate （17.9%）. This work provided an optimized purification method for high recovery of r-fGH, thus contributing to the application of r-fGH to aquaculture.

Stability analysis of underground engineering based on multidisciplinary design optimization

Aiming at characteristics of underground engineering,analyzed the feasibility of Multidisciplinary Design Optimization (MDO) used in underground engineering,and put forward a modularization-based MDO method and the idea of MDO to resolve problems in stability analysis,proving the validity and feasibility of using MDO in underground engi- neering.Characteristics of uncertainty,complexity and nonlinear become bottle-neck to carry on underground engineering stability analysis by MDO.Therefore,the application of MDO in underground engineering stability analysis is still at a stage of exploration,which need some deep research.

Transient reliability optimization for turbine disk radial deformation

The radial deformation design of turbine disk seriously influences the control of gas turbine high pressure turbine(HPT) blade-tip radial running clearance(BTRRC). To improve the design of BTRRC under continuous operation, the nonlinear dynamic reliability optimization of disk radial deformation was implemented based on extremum response surface method(ERSM), including ERSM-based quadratic function(QF-ERSM) and ERSM-based support vector machine of regression(SR-ERSM). The mathematical models of the two methods were established and the framework of reliability-based dynamic design optimization was developed. The numerical experiments demonstrate that the proposed optimization methods have the promising potential in reducing additional design samples and improving computational efficiency with acceptable precision, in which the SR-ERSM emerges more obviously. Through the case study, we find that disk radial deformation is reduced by about 6.5×10–5 m; δ=1.31×10–3 m is optimal for turbine disk radial deformation design and the proposed methods are verified again. The presented efforts provide an effective optimization method for the nonlinear transient design of motion structures for further research, and enrich mechanical reliability design theory.

A Study on Planetary Visual Odometry Optimization： Time Constraints and Reliability

Robust and efficient vision systems are essential in such a way to support different kinds of autonomous robotic behaviors linked to the capability to interact with the surrounding environment, without relying on any a priori knowledge. Within space missions, above all those involving rovers that have to explore planetary surfaces, vision can play a key role in the improvement of autonomous navigation functionalities： besides obstacle avoidance and hazard detection along the traveling, vision can in fact provide accurate motion estimation in order to constantly monitor all paths executed by the rover. The present work basically regards the development of an effective visual odometry system, focusing as much as possible on issues such as continuous operating mode, system speed and reliability.

On the Existence of an Optimal Control of Ship Automatic Steering Instruments

The existence of linear quadratic optimal control of ship automatic steering instruments is studied. Firstly, the sufficient conditions for the quadratic integrability of the solutions of linear second order time-variant differential equations are developed. Secondly, the optimal control form of the ship automatic steering instrument is obtained by using the dynamic programming method, which guarantees a minimal ship sway range, during long-distance navigation, by using as little energy as possible. Finally, based on the above mentioned sufficient conditions, the conditions for the realization of optimal control are obtained, which provides a foundation for choosing the weighted coefficients for optimal control in engineering.

Reliability Optimization in the Islanded Mode of Microgrid

A microgrid is a combination of distributed energy resources and controllable loads. The main objective of this research is to optimize energy flow within a microgrid with regards to reliability in grid connected mode. A microgrid with combined heat and power, natural gas generator, diesel generator, solar energy, wind energy, and battery energy storage along with a critical load is considered in this research. An event oriented analytical method called FTA （fault trees analysis） is implemented for reliability optimization using PTC Windchill Solutions software in a microgrid. The reliability of each component in each energy source of the microgrid is calculated using FTA. The reliability of the critical load is evaluated. The quantitative and qualitative results of FTA are evaluated in order to interpret the results of fault tree. The sensitivity and uncertainty of the fault tree results for critical load is deduced by calculating the importance measures such as risk achievement worth, risk reduction worth, criticality importance and Fussel-Vesely importance. Finally from the results the components that are sensitive and at high risk are deduced.

Optimal transmission lines assignment with maximal reliabilities in multi-source multi-sink multi-state computer network

The optimal transmission lines assignment with maximal reliabilities (OTLAMR) in the multi-source multi-sink multi-state computer network (MMMCN) was investigated. The OTLAMR problem contains two sub-problems: the MMMCN reliabilities evaluation and multi-objective transmission lines assignment optimization. First, a reliability evaluation with a transmission line assignment (RETLA) algorithm is proposed to calculate the MMMCN reliabilities under the cost constraint for a certain transmission lines configuration. Second, the non-dominated sorting genetic algorithm II (NSGA-II) is adopted to find the non-dominated set of the transmission lines assignments based on the reliabilities obtained from the RETLA algorithm. By combining the RETLA and the NSGA-II algorithms together, the RETLA-NSGA II algorithm is proposed to solve the OTLAMR problem. The experiments result show that the RETLA-NSGA II algorithm can provide efficient solutions in a reasonable time, from which the decision makers can choose the best solution based on their preferences and experiences.

Optimization of Routing Considering Uncertainties

A route optimization methodology in the frame of an onboard decision support/guidance system for the ship＇s master has been developed and is presented in this paper. The method aims at the minimization of the fuel voyage cost and the risks related to the ship＇s seakeeping performance expected to be within acceptable limits of voyage duration. Parts of this methodology were implemented by interfacing alternative probability assessment methods, such as Monte Carlo, first order reliability method （FORM） and second order reliability method （SORM）, and a 3-D seakeeping code, including a software tool for the calculation of the added resistance in waves of NTUA-SDL. The entire system was integrated within the probabilistic analysis software PROBAN. Two of the main modules for the calculation of added resistance and the probabilistic assessment for the considered seakeeping hazards with respect to exceedance levels of predefined threshold values are herein elaborated and validation studies proved their efficiency in view of their implementation into an on-board optimization system.

Optimization design of piles subjected to horizontal loads based on reliability theory

Based on reliability theory,a general method for the optimization design of piles subjected to horizontal loads is presented.This method takes into consideration various uncertainties caused by pile installation,variability of geotechnical materials from one location to another,and so on.It also deals with behavior and side constraints specified by standard specifications for piles.To more accurately solve the optimization design model,the first order reliability method is employed.The results from the numerical example indicate that the target reliability index has significant influence on design parameters.In addition,the optimization weight increases with the target reliability index.Especially when the target reliability index is relatively large,the target reliability index has significant influence on design weight of piles.