关于推进地理国情监测“进规划”的思考

当前,地理国情监测制度的"四进"建设是常态化地理国情监测的重要研究内容。"进规划"是"四进"建设中的基础性工作。本文分析了"进规划"的必要性,调研了国家和地方层面地理国情监测"四进"制度中"进规划"的建设进展,分析了目前国家与地方层面"进规划"建设存在的不足与短板,重点对省级推进地理国情监测"进规划"制度建设提出若干建议。

常州市武进城乡规划设计院

常州市武进城乡规划设计院成立于1999年，隶属于常州市规划局，具有城市规划编制丙级资质。自成立以来，随着规模的不断扩大和设计任务的不断增加，我院的设计水平有了较大的提高，已具备了城镇总体规划、专项规划、详细规划、城市设计、市政工程规划等资质范围内一切规划设计的业务能力。

浅析地理国情监测“四进”制度建设

完善的制度与成熟的业务体系是地理国情监测常态化开展的两个必备条件,为此,推进地理国情监测"进法律""进规划""进预算""进职责",建立常态化监测的保障机制十分必要。本文总结了地理国情监测"四进"建设发展现状,探讨分析了目前存在的不足与问题,提出相关建议,以促进常态化地理国情监测顺利开展。

AN APPLICATION OF EVOLUTIONARY PROGRAMMING IN FIR FILTER DESIGN WITH FREQUENCY SAMPLING METHOD

Frequency sampling is one of the popular methods in FIR digital filter design. In the frequency sampling method the value of transition band samples, which are usually obtained by consulting a table, must be determined in order to make the attenuation within the stopband maximal. However, the value obtained by searching for table can not be ensured to be optimal. Evolutionary programming (EP), a multi agent stochastic optimization technique, can lead to global optimal solutions for complex problems. In this paper a new application of EP to frequency sampling method is introduced. Two examples of lowpass and bandpass FIR filters are presented, and the steps of EP realization and experimental results are given. Experimental results show that the value of transition band samples obtained by EP can be ensured to be optimal and the performance of the filter is improved.

AC-PSO ALGORITHM FOR UAV MISSION PLANNING

Choosing the best path during unmanned air vehicle （UAV） flying is the target of the UAV mission planning problem. Because of its nearly constant flight height, the UAV mission planning problem can be treated as a 2-D （horizontal） path arrangement problem. By modeling the antiaircraft threat, the UAV mission planning can be mapped to the traveling seaman problem （TSP）. A new algorithm is presented to solve the TSP. The algorithm combines the traditional ant colony system （ACS） with particle swarm optimization （PSO）, thus being called the AC-PSO algorithm. It uses one by one tour building strategy like ACS to determine that the target point can be chosen like PSO. Experiments show that AC-PSO synthesizes both ACS and PSO and obtains excellent solution of the UAV mission planning with a higher accuracy.

An Evolutionary Programming Based on Hidden Neuron Modifiable Radial Basis Function Networks

In this paper, an improved radial basis function networks named hidden neuron modifiable radial basis function (HNMRBF) networks is proposed for target classification, and evolutionary programming (EP) is used as a learning algorithm to determine and modify the hidden neuron of HNMRBF nets. The result of passive sonar target classification shows that HNMRBF nets can effectively solve the problem of traditional neural networks, i. e. learning new target patterns on line will cause forgetting of the old patterns.

Conservation priority for endemic birds of China's Mainland based on a phylogenetic framework

In this report, a conservation priority scenario for endemic birds of China's Mainland is proposed from a phylogenetic perspective. By utilizing and comparing seven phylogenetic diversity (PD) indices, the study shows that the top ifve endemic birds with high conservation priority are Ar-borophila ardens, A. gingica, A. ruifpectus, Lophophorus lhuysii and Alectoris magna respectively. The ranking of species, based on the IUCN Red List and PD indices, were compared by means of a Wilcox signed rank test and Pearson’s correlation, drawing the inference that the PD ranking of endemic birds for China's Mainland shows a distinct and statistically signiifcant difference from the IUCN rank-ing. Therefore, the ranking of conservation priority for endemic birds of China using PD indices might offer new insights on species conservation from an evolutionary-heritage perspective, serving as a complement to the IUCN ranking.

Three-dimensional multi-constraint route planning of unmanned aerial vehicle low-altitude penetration based on coevolutionary multi-agent genetic algorithm

To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.

Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems

In this paper, an improved hybrid differential evolution-estimation of distribution algorithm (IHDE-EDA) is proposed for nonlinear programming (NLP) and mixed integer nonlinear programming (MINLP) models in engineering optimization fields. In order to improve the global searching ability and convergence speed, IHDE-EDA takes full advantage of differential information and global statistical information extracted respectively from differential evolution algorithm and annealing mechanism-embedded estimation of distribution algorithm. Moreover, the feasibility rules are used to handle constraints, which do not require additional parameters and can guide the population to the feasible region quickly. The effectiveness of hybridization mechanism of IHDE-EDA is first discussed, and then simulation and comparison based on three benchmark problems demonstrate the efficiency, accuracy and robustness of IHDE-EDA. Finally, optimization on an industrial-size scheduling of two-pipeline crude oil blending problem shows the practical applicability of IHDE-EDA.

Multi-objective evolutionary approach for UAV cruise route planning to collect traffic information

Unmanned aerial vehicle(UAV)was introduced as a novel traffic device to collect road traffic information and its cruise route planning problem was considered.Firstly,a multi-objective optimization model was proposed aiming at minimizing the total cruise distance and the number of UAVs used,which used UAV maximum cruise distance,the number of UAVs available and time window of each monitored target as constraints.Then,a novel multi-objective evolutionary algorithm was proposed.Next,a case study with three time window scenarios was implemented.The results show that both the total cruise distance and the number of UAVs used continue to increase with the time window constraint becoming narrower.Compared with the initial optimal solutions,the optimal total cruise distance and the number of UAVs used fall by an average of 30.93% and 31.74%,respectively.Finally,some concerns using UAV to collect road traffic information were discussed.

Bounded space algorithms for variant of variable-sized bin packing

Given a list of items and a sequence of variable-sized bins arriving one by one, it is NP-hard to pack the items into the bin list with a goal to minimize the total size of bins from the earliest one to the last used. In this paper a set of approximation algorithms is presented for cases in which the ability to preview at most k（〉=2） arriving bins is given. With the essential assumption that all bin sizes are not less than the largest item size, analytical results show the asymptotic worst case ratios of all k-bounded space and offiine algorithms are 2. Based on experiments by applying algorithms to instances in which item sizes and bin sizes are drawn independently from the continuous uniform distribution respectively in the interval [0,u] and [u,l ], averagecase experimental results show that, with fixed k, algorithms with the Best Fit packing（closing） rule are statistically better than those with the First Fit packing（closing） rule.

卷烟厂制丝生产仿真与APS应用

根据卷烟生产工艺及产品特点,针对高级计划排程算法面临的解可靠性、可行性问题,基于排程软件的客制化程序接口,通过软件自带算法及遗传算法,设计了卷烟厂制丝生产计划算法模型.采用仿真软件构建制丝生产线仿真模型的基础上,对制丝生产计划排程算法模型和技术方案进行了研究,并采用实际生产数据对模型及技术方案的有效性进行了验证.结果表明:实验各批次均完成了任务;进阶生产规划及排程系统的应用,使某卷烟厂膨丝计划量比生产需求目标提高了18.3%,生产线设备高效低耗;排程算法模型和技术方案切实可行;进阶生产规划及排程系统的应用有助于实现卷烟生产的全面智能排程.

Evolutional Algorithm Based Cascade Long Reach Passive Optical Networks Planning

In this paper, we propose a mathe- matical model for long reach Passive Optical Networks （PON） planning. The model consid- ers the traffic demand, user requirements and physical constraints. It can support conven- tional star-like topologies as well as cascade PON networks. Then a two-stage evolutional algorithm is described to solve this problem. The first stage was to find a proper splitter can- didate site set, composing the outer loop. The second stage aimed to get the optimal topology when the splitter locations were selected, com- posing the internal loop. In this algorithm, the Pr/ifer sequence is used to build up a one-to-one correspondence between a PON network configuration and a chromosome. Compared with the results obtained by the enumeration method, the proposed model and algorithm are shown to be effective and accu- rate.

An Approach to Formulation of FNLP with Complex Piecewise Linear Membership Functions

Traditionally, extra binary variables are demanded to formulate a fuzzy nonlinear programming(FNLP) problem with piecewise linear membership functions(PLMFs). However, this kind of methodology usually suffers increasing computational burden associated with formulation and solution, particularly in the face of complex PLMFs. Motivated by these challenges, this contribution introduces a novel approach free of additional binary variables to formulate FNLP with complex PLMFs, leading to superior performance in reducing computational complexity as well as simplifying formulation. A depth discussion about the approach is conducted in this paper, along with a numerical case study to demonstrate its potential benefits.

Bilevel Programming Model for Joint Scheduling of Arrival and Departure Flights Based on Traffic Scenario

In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of arrival and departure flights is studied systematically.According to the matching degree of capacity and flow,it is determined that the traffic state of arrival/departure operation in a certain period is peak or off-peak.The demands of all parties in each traffic state are analyzed,and the mathematical models of arrival/departure flight scheduling in each traffic state are established.Aiming at the four kinds of joint operation traffic scenarios of arrival and departure,the corresponding bi-level programming models for joint scheduling of arrival and departure flights are established,respectively,and the elitism genetic algorithm is designed to solve the models.The results show that:Compared with the first-come-firstserved method,in the scenarios of arrival peak&departure off-peak and arrival peak&departure peak,the departure flight equilibrium satisfaction is improved,and the runway occupation time of departure flight flow is reduced by 38.8%.In the scenarios of arrival off-peak&departure off-peak and departure peak&arrival off-peak,the arrival flight equilibrium delay time is significantly reduced,the departure flight equilibrium satisfaction is improved by 77.6%,and the runway occupation time of departure flight flow is reduced by 46.6%.Compared with other four kinds of strategies,the optimal scheduling method can better balance fairness and efficiency,so the scheduling results are more reasonable.

Station Cone Algorithm for Linear Programming

Recently we have proposed anew method combininginterior and exterior approaches to solve linear programming problems. This method uses an interior point, and from there connected to the vertex of the so called station cone which is also a solution of the dual problem. This allows us to determine the entering vector and the new station cone. Here in this paper, we present a new modified algorithm for the case, when at each iteration we determine a new interior point. The new building interior point moves toward the optimal vertex. Thanks to the shortened from both inside and outside, the new version allows to find quicker the optimal solution. The computational experiments show that the number of iterations of the new modified algorithm is significantly smaller than that of the second phase of the dual simplex method.

Planning Sustainable Consumption and Quality of Life in the Baku City

The study of sustainable consumption （SC） and quality of life （QoL） in Baku City was undertaken as part of the Baku Strategic Plan prepared by the Department of Architecture and Urban Planning, Azerbaijan Architecture and Construction University, and partially supported by the Society of Urbanists of Azerbaijan, Research Group. The key purpose of the research was to provide useful information for developing planning and design strategies that would foster sustainable urbanization through enhancing QoL and consumption, which was one of the most important principles of sustainable urbanization. Another purpose was to explore the impact of environmental, economic, social, physical, and health-related indicators on SC and QoL satisfaction among Baku residents. Ultimately, the research will provide recommendations which will further enhance the SC and QoL in Baku City at a number of levels, from empowering communities at a local level to participate in the evolution of their neighborhoods to influence institutional and corporate objectives and sustainability policies. The information collated will feed into the Baku Strategic Planning Process and help to determine developed strategies for urban development and urban regeneration.

Instruments of Urban Planning in Algerian City： Reality and Challenges

The year 1990 marks a line of rupture in the history of Algeria in general by the fundamental changes that have occurred, especially in the fields of urbanism and the land use planning, which has an important impact on space of the city and its environment. However, the absence of directives based on the reality of upstream territories and sometimes the conflict and the weakness of the instruments created at different levels： national, regional and local, have accelerated the galloping development of urbanization （the irrational consumption of land reserves inside and around the city）, often at the expense of the agricultural land. On the other hand, the involvement of new actors in the production of the framework built in the Algerian town was made without compliance with the rules of architecture and urbanism contained in the build permit and in the MPU （Master Plan of Land Use and Urbanism） and the SOP （Soil Occupation Plan） approved. The analyses conducted in the cities such as the capital Algiers and Setif illustrate this situation well. This article presents these situations of paradox, identifies their causes and suggests the recommendations to implement in the framework of studies and actions to take, to correct and regulate their mutations.

To Withstand Loneliness in the Process of Urbanization——Research on the Construction and Planning of Metropolitan Suburban Rural Tourism Scenic Areas

Abstract The conflicts between rurality and urbanization,tradition and modernity,industry and environmental resource in the rural tourism have become major difficulties of its sustainable development in China.This paper analyzed the characteristics and difficult situations of metropolitan suburban rural tourism,put forward four kinds of region-city functions in the development of metropolitan suburban rural tourism,and researched on the construction of rural tourism scenic areas in metropolis suburb—"to Withstand Loneliness in the Process of Urbanization"—as the following aspects:the space organization mode,localization,social organization and management,the product organization and spatial planning modes and contents.

Dynamic reactive power planning method for CSP-PV hybrid power generation system

Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulation capability of the system itself.We propose a dynamic reactive power planning method suitable for CSP-PV hybrid power generation system.The method determines the installation node of the dynamic reactive power compensation device and its compensation capacity based on the reactive power adjustment capability of the system itself.The critical fault node is determined by the transient voltage stability recovery index,and the weak node of the system is initially determined.Based on this,the sensitivity index is used to determine the installation node of the dynamic reactive power compensation device.Dynamic reactive power planning optimization model is established with the lowest investment cost of dynamic reactive power compensation device and the improvement of system transient voltage stability.Furthermore,the component of the reactive power compensation node is optimized by particle swarm optimization based on differential evolution(DE-PSO).The simulation results of the example system show that compared with the dynamic position compensation device installation location optimization method,the proposed method can improve the transient voltage stability of the system under the same reactive power compensation cost.