Integrated Approach to the Vital Mechanism Theory and Ant Colony Algorithm for Optimized Land Use Allocation: A Case Study of the Liangjiang New Area in Chongqing

Optimal allocation of land use is essential to promote regional economic and social development.However,research on such allocations in development zones is limited.This paper proposes a new land use allocation method for development zones and tests its feasibility.Based on prior research,this study predicts the developmental stage of a development zone and sets the objective functions and constraint conditions accordingly.This paper then measures the conversion relationship between the land use types in an unit according to the land use suitability results and the vital mechanism theory and uses the ant colony algorithm to construct a land use optimization model on the basis of this conversion relatonship.The model is then applied successfully to a case study of the Liangjiang New Area,Chongqing,China.The results show that the vital mechanism theory better reflects the relationship between land use types.The economic benefits increase 3.5 times and compactness improves by 46.5%between the initial year(2009)and the optimized year(2020),after the proposed model is applied.

Exploring Smart Growth Boundaries of Urban Agglomeration with Land Use Spatial Optimization:A Case Study of Changsha-Zhuzhou-Xiangtan City Group,China

Urban agglomeration is the main spatial organization mode used by the Chinese government to promote the policy of new urbanization strategy.Hence,a better understanding of the urban growth boundary(UGB)has profound theoretical and practical significance regarding sustainable urban development.This study devised a raster-based land use spatial optimization(LUSO)framework,and utilized ant colony optimization(ACO)algorithm to delimit the smart growth boundaries of the Changsha-Zhuzhou-Xiangtan city group(CZTCG)in China.The aim of this study is to design a LUSO model to explore an optimal pattern of urban agglomeration for sustainable growth.Multi growth scenario including a single development center,multipolar development and balanced development patterns are generated by the LUSO model for the year of 2050,and the optimum spatial pattern is chosen based on objectives comparison and the present stage of economic and social development in CZTCG.The main results are listed as the following.1)It is feasible to identify the growth boundaries of the urban agglomeration using the land use spatial optimization model,and the optimal form of the spatial pattern can be defined.2)With the growth trend of the urban agglomeration gradually spreads from a single center to multi-centers and even small towns,the total optimization target performance gradually increases,which means that the traditional pie-shaped development does not meet the maximum comprehensive benefit of the city group.3)Subject to the regional social and economic development stage,absolute fair development or simply developing the central city is not conducive to promoting the coordinated development of the urban agglomeration.Gradient equalization and gradual advancement are the best choice for UGB delineation of urban agglomeration.The findings of this study would be useful to identify the UGB in CZTCG for more sustainable urban development in the future.

Optimization and Regulation Policy for Land Use Changes Based on Low-carbon Emission in Developed Regions of China

Land use and cover change(LUCC) is one of the important causes of the Earth’s carbon cycle imbalances resulting from failure in optimizing land use. The solution to this problem has been the hotspot of research in land and environmental science. We took 'low carbon', 'energy saving' and 'high-efficiency' as the goals of land use optimization,and integrated Markov-CA(Cellular Automaton),the Grid-Fractal model and GIS,in order to study carbon emission objective function,to establish a simulation method for land use spatial allocation optimization,to evaluate the effect of the method on carbon emissions. Regulation policy on three types of land use spatial allocation was proposed,including 'low-carbon type', 'low-carbon-economic type' and 'economic type'. We applied the method to analyze the land use spatial allocation in Taixing City of the 'Yangtze River Delta' regions in China,and obtained the following results:(i) The three optimization types would improve carbon emissions by 3. 21%,1. 80% and 0. 36% respectively in 2020,compared with 2010;(ii) The actual planning for 2020 was close to the 'low-carbon-economic type';(iii) The optimization method and regulation policy,combining local optimization and global control,could meet the sustainable multi-objective requirements for low-carbon constraints of land use spatial allocation. The result of this research could also serve as a reference for exploration into patterns of regional low-carbon land use and measures for energy saving and emission reduction.

Optimized Reimbursement Scheme of China's New Cooperative Medical System Using Monte Carlo Simulation

China＇s Rural Cooperative Medical System collapsed alongside communal farming at the end of the Maoist period in 1976, leaving most farmers vulnerable[1]. In rural areas, where 80% of people have been without health insurance of any kind, illness has emerged as a leading cause of poverty[24]. To address the poor state of health care among the rural population, in 2003 the Chinese government launched the New Rural Cooperative Medical System （NCMS）,

Current Research Situations,Problems and Recommendations of Land Use Structure and Layout Optimization

Land is the foundation for human survival and development,and all human social and economic activities are inseparable from the land as a space carrier.With the continuous development of China's social economy,China is facing new social development needs such as urban-rural integration and rural revitalization.At the same time,China starts to attach great importance to ecology and has proposed the concept that lucid waters and lush mountains are invaluable assets.In this situation,the rational use of land resources,the optimization of land use structure and layout are also facing new challenges and problems,and more comprehensive consideration is required to make relevant optimization.Using the method of literature comparative analysis,from the conceptual connotation,basic theory,method model,and specific practice of land use structure and layout optimization,this paper analyzed and summarized the current research situations and problems,and finally came up with recommendations for the future research.

森林优化特征选择算法的增强与扩展

特征选择作为一种重要的数据预处理方法,不但能解决维数灾难问题,还能提高算法的泛化能力.各种各样的方法已被应用于解决特征选择问题,其中,基于演化计算的特征选择算法近年来获得了更多的关注并取得了一些成功.近期研究结果表明,森林优化特征选择算法具有更好的分类性能及维度缩减能力.然而,初始化阶段的随机性、全局播种阶段的人为参数设定,影响了该算法的准确率和维度缩减能力;同时,算法本身存在着高维数据处理能力不足的本质缺陷.从信息增益率的角度给出了一种初始化策略,在全局播种阶段,借用模拟退火控温函数的思想自动生成参数,并结合维度缩减率给出了适应度函数;同时,针对形成的优质森林采取贪心算法,形成一种特征选择算法EFSFOA(enhanced feature selection using forest optimization algorithm).此外,在面对高维数据的处理时,采用集成特征选择的方案形成了一个适用于EFSFOA的集成特征选择框架,使其能够有效处理高维数据特征选择问题.通过设计对比实验,验证了EFSFOA与FSFOA相比在分类准确率和维度缩减率上均有明显的提高,高维数据处理能力更是提高到了100 000维.将EFSFOA与近年来提出的比较高效的基于演化计算的特征选择方法进行对比,EFSFOA仍具有很强的竞争力.

Adaptive Particle Swarm Optimization Data Hiding for High Security Secret Image Sharing

The main aim of this work is to improve the security of data hiding forsecret image sharing. The privacy and security of digital information have becomea primary concern nowadays due to the enormous usage of digital technology.The security and the privacy of users’ images are ensured through reversible datahiding techniques. The efficiency of the existing data hiding techniques did notprovide optimum performance with multiple end nodes. These issues are solvedby using Separable Data Hiding and Adaptive Particle Swarm Optimization(SDHAPSO) algorithm to attain optimal performance. Image encryption, dataembedding, data extraction/image recovery are the main phases of the proposedapproach. DFT is generally used to extract the transform coefficient matrix fromthe original image. DFT coefficients are in float format, which assists in transforming the image to integral format using the round function. After obtainingthe encrypted image by data-hider, additional data embedding is formulated intohigh-frequency coefficients. The proposed SDHAPSO is mainly utilized for performance improvement through optimal pixel location selection within the imagefor secret bits concealment. In addition, the secret data embedding capacityenhancement is focused on image visual quality maintenance. Hence, it isobserved from the simulation results that the proposed SDHAPSO techniqueoffers high-level security outcomes with respect to higher PSNR, security level,lesser MSE and higher correlation than existing techniques. Hence, enhancedsensitive information protection is attained, which improves the overall systemperformance.

Optimizing Domain Distribution of Grain Oriented Silicon Steel by Using Antimony as the Laser Surface Alloying Element

For reducing the core loss of grain oriented silicon steel and improving its aging property, a new method, the LLSA by using Sb as the laser surface alloying element, was investigated, and at proper technique conditions rather good result was obtained.

A useful method for determination of optimal fiber input power in spontaneous Brillouin-scattering-based sensing system

A method for the optimal fiber input power determination is presented by employing the variation characteristics of signal to noise ratio(SNR) in spontaneous Brillouin-scattering-based sensing system. And a heterodyne detection system is constructed for measuring the Brillouin scattering spectra with different fiber input powers. The Brillouin spectrum width and system SNR can be simultaneously measured from these spectra, and the optimal fiber input power can be obtained from such information. In the experiment, for 48.8-km-long standard single-mode fiber(SSMF), the optimal fiber input power values are all approximately 0 dBm obtained by the maximum SNR position for different local oscillator power values and average times.

Optimization design of the angle detecting system used in the fast steering mirror

In this paper, in order to design a fast steering mirror(FSM) with large deflection angle and high linearity, a deflection angle detecting system(DADS) using quadrant detector(QD) is developed. And the mathematical model describing DADS is established by analyzing the principle of position detecting and error characteristics of QD. Based on this mathematical model, the variation tendencies of deflection angle and linearity of FSM are simulated. Then, by changing the parameters of the DADS, the optimization of deflection angle and linearity of FSM is demonstrated. Finally, a QD-based FSM is designed based on this method, which achieves ±2° deflection angle and 0.72% and 0.68% linearity along x and y axis, respectively. Moreover, this method will be beneficial to the design of large deflection angle and high linearity FSM.

An experiment for obtaining DOP ellipsoid using particle swarm optimization algorithm

The degree of polarization (DOP) ellipsoid can be used as either feedback or feedforward signal for automatic polarization mode dispersion compensation. We have realized the experiment for obtaining DOP ellipsoid from 100 sampling data of output states of polarization using particle swarm optimization (PSO) as ellipsoid data fitting algorithm. It was shown that the PSO algorithm was powerful for ellipsoid data fitting with high precision within 250 ms.

Towards the sustainable intensification of agriculture——a systems approach to policy formulation

The sustainable intensification of agriculture involves providing sufficient food and other ecosystem services without going beyond the limits of the earth’s system.Here a project management approach is suggested to help guide agricultural policy to deliver these objectives.The first step is to agree measurable outcomes,integrating formal policy goals with the often much less formal and much more diverse goals of individual farmers.The second step is to assess current performance.Ideally,this will involve the use of farm-scale metrics that can feed into process models that address social and environmental domains as well as production issues that can be benchmarked and upscaled to landscape and country.Some policy goals can be delivered by supporting ad hoc interventions,while others require the redesign of the farming system.A pipeline of research,knowledge and capacity building is needed to ensure the continuous increase in farm performance.System models can help prioritise policy interventions.Formal optimization of land use is only appropriate if the policy goals are clear,and the constraints understood.In practice,the best approach may depend on the scale of action that is required,and on the amount of resource and infrastructure available to generate,implement and manage policy.

Gain Flattened Raman Fiber Amplifier Using Parameter Optimization and DCF Fiber

We investigate two configurations of Raman fiber amplifier in the 1530-1570 nm region. The gain spectrum variation is decreased from 8.31 dB to 2.48 dB when appropriately adjust the individual two pumps and optical fiber.

Optimization of multicomponent solvent selection in high-performance liquid chromatography using a statistical method

A computer-assisted method is presented for optimization of multicomponent solvent mobile phase selection for separation of O-ethyl-N-isopropyl phosphoro(thioureido)thioates in reversed-phase HPLC and four geometric isomers of pesticides Decis in normal-phase HPLC.The method is based on Snyder's solvent selection triangle concept using a statistical method.The optimization of the separation over the experimental region is based on a special polynomial esti- mation from seven experimental runs,and resolution(R_s)is used as the selection criterion.Excellent agreement was obtained between predicted data and experimental results.