我国环境质量法规模型体系建设对策与建议

模型的法规化建设对于提高环境管理决策的科学性,保证法规性文件的一致性,减少因采用的模型差异而造成的差别管理等不公平因素起着重要作用。通过介绍国内外环境质量模型法规化现状,并结合我国环境质量模型法规化现状与问题,提出了我国环境质量法规模型建设方案与建议。

Cooperative merging control strategy of connected and automated vehicles on highways

To improve traffic performance when on-ramp vehicles merge into the mainstream,a collaborative merging control strategy is proposed to determine the merging sequence and trajectory control of vehicles.Merging trajectory planning takes the minimization of vehicle acceleration as the optimization objective.Either the variational method or the quadratic programming method is utilized to determine arrival time,optimal time and control variables for each vehicle.As a supplement,the adaptive cruise control(ACC)model is used to calculate each control variable in each time interval on special occasions.Simulation results show that the cooperative merging control strategy outperforms the optimal control strategy.The root mean square(RMS)of acceleration and the root mean square error(RMSE)of time headway are significantly decreased,with the reductions up to 90.1%and 25.2%,respectively.Under the cooperative control strategy,the difference between the average speed and desired speed consistently approaches zero.In addition,few or no collisions occur.To conclude,the proposed strategy favours the improvements in passenger comfort,traffic efficiency,traffic stability and safety around highway on-ramps.

Two-stage stochastic approach for spinning reserve allocation in dynamic economic dispatch

A novel approach was proposed to allocate spinning reserve for dynamic economic dispatch.The proposed approach set up a two-stage stochastic programming model to allocate reserve.The model was solved using a decomposed algorithm based on Benders' decomposition.The model and the algorithm were applied to a simple 3-node system and an actual 445-node system for verification,respectively.Test results show that the model can save 84.5 US $ cost for the testing three-node system,and the algorithm can solve the model for 445-node system within 5 min.The test results also illustrate that the proposed approach is efficient and suitable for large system calculation.

Buffer allocation method of serial production lines based on improved ant colony optimization algorithm

Buffer influences the performance of production lines greatly.To solve the buffer allocation problem(BAP) in serial production lines with unreliable machines effectively,an optimization method is proposed based on an improved ant colony optimization(IACO) algorithm.Firstly,a problem domain describing buffer allocation is structured.Then a mathematical programming model is established with an objective of maximizing throughput rate of the production line.On the basis of the descriptions mentioned above,combining with a two-opt strategy and an acceptance probability rule,an IACO algorithm is built to solve the BAP.Finally,the simulation experiments are designed to evaluate the proposed algorithm.The results indicate that the IACO algorithm is valid and practical.

Soil Quality Assessment Using Weighted Fuzzy Association Rules

Fuzzy association rules (FARs) can be powerful in assessing regional soil quality, a critical step prior to land planning and utilization; however, traditional FARs mined from soil quality database, ignoring the importance variability of the rules, can be redundant and far from optimal. In this study, we developed a method applying different weights to traditional FARs to improve accuracy of soil quality assessment. After the FARs for soil quality assessment were mined, redundant rules were eliminated according to whether the rules were significant or not in reducing the complexity of the soil quality assessment models and in improving the comprehensibility of FARs. The global weights, each representing the importance of a FAR in soil quality assessment, were then introduced and refined using a gradient descent optimization method. This method was applied to the assessment of soil resources conditions in Guangdong Province, China. The new approach had an accuracy of 87%, when 15 rules were mined, as compared with 76% from the traditional approach. The accuracy increased to 96% when 32 rules were mined, in contrast to 88% from the traditional approach. These results demonstrated an improved comprehensibility of FARs and a high accuracy of the proposed method.

Landslide susceptibility mapping using Genetic Algorithm for the Rule Set Production(GARP) model

Investigation on landslide phenomenon is necessary for understanding and delineating the landslide prone and safer places for different land use practices. On this basis, a new model known as genetic algorithm for the rule set production was applied in order to assess its efficacy to obtain a better result and a more precise landslide susceptibility map in Klijanerestagh area of Iran. This study considered twelve landslide conditioning factors(LCF) like altitude, slope, aspect, plan curvature, profile curvature, topographic wetness index(TWI), distance from rivers, faults, and roads, land use/cover, and lithology. For modeling purpose, the Genetic Algorithm for the Rule Set Production(GARP) algorithm was applied in order to produce the landslide susceptibility map. Finally, to evaluate the efficacy of the GARP model, receiver operating characteristics curve as well as the Kappa index were employed. Based on these indices, the GARP model predicted the probability of future landslide incidences with the area under the receiver operating characteristics curve(AUC-ROC) values of 0.932, and 0.907 for training and validating datasets, respectively. In addition, Kappa values for the training and validating datasets were computed as 0.775, and 0.716, respectively. Thus, it can be concluded that the GARP algorithm can be a new but effective method for generating landslide susceptibility maps(LSMs). Furthermore, higher contribution of the lithology, distance from roads, and distance from faults was observed, while lower contribution was attributed to soil, profile curvature, and TWI factors. The introduced methodology in this paper can be suggested for other areas with similar topographical and hydrogeological characteristics for land use planning and reducing the landslide damages.

Tourist Route Model Formulation Method Considering Spatial Reproducibility

This study aims to gradually reflect information concerning tourists and to propose tourist route model formulation techniques that take spatial reproducibility into account using GIS （geographic information systems）. The conclusions can be summarized into the following three points： （1） Kawagoe city in Saitama Prefecture was selected as the area targeted by this study. All types of data about Kawagoe city and tourists was collected and processed, and a tourist route model formulation method that considered spatial reproducibility using GIS was proposed, （2） 3-stage scenarios were created with the presence or absence of Kawagoe city tourist policies set as standards and this was used to develop tourist route models. It is POSsible to expect synergy in the encouragement of the use of sightseeing buses and the same traffic regulations as the traffic pilot program, and （3） It is considered that it is possible to apply the tourist route model formulation method proposed by this study to other tourist destinations without being limited by spatiotemporal differences or the particular issues of each tourist destinations as spatial reproducibility was confirmed.

Modeling and Optimization for Short-term Scheduling of Multipurpose Batch Plants

In the past two decades, short-term scheduling of multipurpose batch plants has received significant attention. Most scheduling problems are modeled using either state-task-network or resource-task-network(RTN) process representation. In this paper, an improved mixed integer linear programming model for short-term schedul-ing of multipurpose batch plants under maximization of profit is proposed based on RTN representation and unit-specific events. To solve the model, a hybrid algorithm based on line-up competition algorithm and linear programming is presented. The proposed model and hybrid algorithm are applied to two benchmark examples in literature. The simulation results show that the proposed model and hybrid algorithm are effective for short-term scheduling of multipurpose batch plants.

An inverse method for online stress monitoring and fatigue life analysis of boiler drums

A method based on solution of the inverse heat conduction problem was presented for online stress monitoring and fatigue life analysis of boiler drums. The mathematical model of the drum temperature distribution is based on the assumptions that the difference of temperature along the longitudinal axis of the boiler drum is negligible with changes only in the radial direction and the circumferential direction, and that the outer surface of drum is thermaUy insulated. Combining this model with the control-volume method provides temperatures at different points on a cross-section of the drum. With the temperature data, the stresses and the life expectancy of the boiler drum are derived according to the ASME code. Applying this method to the cold start-up process of a 300 MW boiler demonstrated the absence of errors caused by the boundary condition assumptions on the inner surface of the drum and testified that the method is an applicable technique for the online stress monitoring and fatigue life analysis of boiler drums.

Needs of thermodynamic properties measurements and modeling in the frame of new regulations on refrigerants

In 1987, the Montreal Protocol prohibited the worldwide use and production of chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs) and hydro fluorocarbons (HFCs) were proposed as alternative refrigerants. Unfortunately, HFCs have non negligible global warning potential and therefore new refrigerants must be proposed or old refrigerants must be used associated with HFC. Accurate experimental thermodynamic data and predictive techniques are required for better under-standing of the performance of the newly proposed refrigerants. In this communication, experimental techniques based on either analytic or synthetic methods are first described. Data are reported. Then two newly developed predictive models based on thermodynamic approach with the isofugacity criterion and artificial neural network method are presented. The results can provide better evaluation of refrigerants, especially with the aim of studying global warning effects.

Multidisciplinary design optimization on production scale of underground metal mine

In order to ensure overall optimization of the underground metal mine production scale, multidisciplinary design optimization model of production scale which covers the subsystem objective function of income of production, safety and environmental impact in the underground metal mine was established by using multidisciplinary design optimization method. The coupling effects from various disciplines were fully considered, and adaptive mutative scale chaos immunization optimization algorithm was adopted to solve multidisciplinary design optimization model of underground metal mine production scale. Practical results show that multidisciplinary design optimization on production scale of an underground lead and zinc mine reflect the actual operating conditions more realistically, the production scale is about 1.25 Mt/a (Lead and zinc metal content of 160 000 t/a), the economic life is approximately 14 a, corresponding coefficient of production profits can be increased to 15.13%, safety factor can be increased to 5.4% and environmental impact coefficient can be reduced by 9.52%.

Dynamic formation control for autonomous underwater vehicles

Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which several algorithms were developed for the complex underwater environment.Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes.Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles.Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation.The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated.Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness,even with a concave obstacle.It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.

Equation oriented method for Rectisol wash modeling and analysis

Rectisol process is more efficient in comparison with other physical or chemical absorption methods for gas purification. To implement a real time simulation of Rectisol process, thermodynamic model and simulation strategy are needed. In this paper, a method of modified statistical associated fluid theory with perturbation theory is used to predict thermodynamic behavior of process. As Rectisol process is a highly heat-integrated process with many loops, a method of equation oriented strategy, sequential quadratic programming, is used as the solver and the process converges perfectly. Then analyses are conducted with this simulator.

Pitch models of Mandarin text-to-speech

The function of prosody model will directly affect the naturalness of synthesized speech.Aimed at the difficulty in generating the pitch contour in prosody model,two pitch models namely corpus-based pitch model and pitch pattern model are deeply studied in this paper.Key problems in the corpus-based model are calculation of the distance and searching of the optimal path with dynamic programming algorithm.For the pitch pattern model,parameters such as pitch pattern,pitch average and pitch range are used to describe the pitch contour,and six pitch patterns are presented.For the generation of pitch contour,the pitch pattern model is more flexible than the corpus-based model.Both of the two models are linked to the real TTS system,and the MOS results of synthesized Mandarin speech show that the pitch pattern model is better than the corpus-based pitch model.

Confidence Level Based on Ridge Estimator in Process Measurement and Its Application

Ordinary least squares(OLS) algorithm is widely applied in process measurement, because the sensor model used to estimate unknown parameters can be approximated through multivariate linear model. However, with few or noisy data or multi-collinearity, unbiased OLS leads to large variance. Biased estimators, especially ridge estimator, have been introduced to improve OLS by trading bias for variance. Ridge estimator is feasible as an estimator with smaller variance. At the same confidence level, with additive noise as the normal random variable, the less variance one estimator has, the shorter the two-sided symmetric confidence interval is. However, this finding is limited to the unbiased estimator and few studies analyze and compare the confidence levels between ridge estimator and OLS. This paper derives the matrix of ridge parameters under necessary and sufficient conditions based on which ridge estimator is superior to OLS in terms of mean squares error matrix, rather than mean squares error.Then the confidence levels between ridge estimator and OLS are compared under the condition of OLS fixed symmetric confidence interval, rather than the criteria for evaluating the validity of different unbiased estimators. We conclude that the confidence level of ridge estimator can not be directly compared with that of OLS based on the criteria available for unbiased estimators, which is verified by a simulation and a laboratory scale experiment on a single parameter measurement.

Filtered-beam-search-based approach for operating theatre scheduling

To improve the efficiency of operating rooms, reduce the hospital＇ s costs and improve the level of service qualities, a scheduling method is presented based on a filtered-beam-search-based algo- rithm. Firstly, a scheduling problem domain is described. Mathematical programming models are al- so set up with an objective function of minimizing related costs of the system. On the basis of the de= scriptions mentioned above, a solving policy of generating feasible scheduling solutions is estab- lished. Combining with the speeific constraints of operation theatres, a filtered-beam-search-based algorithm is put forward to solve scheduling problems. Finally, simulation experiments are designed. The performance of the proposed algorithm is evaluated and compared with that of other approaches through simulations. Results indicate that the proposed algorithm can reduce costs, and are of prac- ticality and effectiveness.

Research on the Applications of Cyclic Water Quality Model and Simulated Annealing Algorithm for Water Pollution Control and Planning

With the progress of computer technology, water pollution control and planning has been a hot topic in the scientific community. This paper discusses corresponding research on the applications of cyclic water quality model and simulated annealing algorithm for water pollution control and planning. Environmental engineering education has been the focus of much attention in recent years. Teaching methods of water pollution control and sustainable teaching innovation and creation was explored by many scholars, and the majority of workers engaged in teaching the course. The simulation result proves the effectiveness of the method. We plan to conduct more research in the future research to obtain better research result.

Multi-objective optimization of space station short-term mission planning

This paper studies the multi-objective optimization of space station short-term mission planning(STMP), which aims to obtain a mission-execution plan satisfying multiple planning demands. The planning needs to allocate the execution time effectively, schedule the on-board astronauts properly, and arrange the devices reasonably. The STMP concept models for problem definitions and descriptions are presented, and then an STMP multi-objective planning model is developed. To optimize the STMP problem, a Non-dominated Sorting Genetic Algorithm II(NSGA-II) is adopted and then improved by incorporating an iterative conflict-repair strategy based on domain knowledge. The proposed approach is demonstrated by using a test case with thirty-five missions, eighteen devices and three astronauts. The results show that the established STMP model is effective, and the improved NSGA-II can successfully obtain the multi-objective optimal plans satisfying all constraints considered. Moreover, through contrast tests on solving the STMP problem, the NSGA-II shows a very competitive performance with respect to the Strength Pareto Evolutionary Algorithm II(SPEA-II) and the Multi-objective Particle Swarm Optimization(MOPSO).

An iterative interval analysis method based on Kriging-HDMR for uncertainty problems

In recent years,growing attention has been paid to the interval investigation of uncertainty problems.However,the contradiction between accuracy and efficiency always exists.In this paper,an iterative interval analysis method based on Kriging-HDMR(IIAMKH)is proposed to obtain the lower and upper bounds of uncertainty problems considering interval variables.Firstly,Kriging-HDMR method is adopted to establish the meta-model of the response function.Then,the Genetic Algorithm&Sequential Quadratic Programing(GA&SQP)hybrid optimization method is applied to search for the minimum/maximum values of the meta-model,and thus the corresponding uncertain parameters can be obtained.By substituting them into the response function,we can acquire the predicted interval.Finally,an iterative process is developed to improve the accuracy and stability of the proposed method.Several numerical examples are investigated to demonstrate the effectiveness of the proposed method.Simulation results indicate that the presented IIAMKH can obtain more accurate results with fewer samples.

CIVB flashback analysis of hydrogen flame based on azimuthal vorticity at mixing zone exit

Swirl-premixed combustion systems exhibit potential to meet future regulations on pollution emissions. However, combustion induced vortex breakdown(CIVB) flashback is frequently observed in these systems, especially for high hydrogen content fuel. In this study, a swirl-premixed burner with diverging centerbody was used to investigate CIVB flashback based on azimuthal vorticity at mixing zone exit. Through 2D axisymmetric model, it was found that there was a maximal azimuthal vorticity at mixing zone exit for each equivalence ratio. The physical meaning of these maximal azimuthal vorticity values was the minimally required azimuthal vorticity to trigger CIVB flashback. At the same time, the required azimuthal vorticity declined with the increase of equivalence ratio since turbulent burning velocity started to control flashback. Nevertheless, azimuthal vorticity offered by heat release increased with the increase of equivalence ratio, which promoted flame propagating upstream continually.