Analysis of the inflection points of height-diameter models

The inflection point is an important feature of sigmoidal height-diameter(H-D)models.It is often cited as one of the properties favoring sigmoidal model forms.However,there are very few studies analyzing the inflection points of H-D models.The goals of this study were to theoretically and empirically examine the behaviors of inflection points of six common H-D models with a regional dataset.The six models were the Wykoff(WYK),Schumacher(SCH),Curtis(CUR),HossfeldⅣ(HOS),von Bertalanffy-Richards(VBR),and Gompertz(GPZ)models.The models were first fitted in their base forms with tree species as random effects and were then expanded to include functional traits and spatial distribution.The distributions of the estimated inflection points were similar between the two-parameter models WYK,SCH,and CUR,but were different between the threeparameter models HOS,VBR,and GPZ.GPZ produced some of the largest inflection points.HOS and VBR produced concave H-D curves without inflection points for 12.7%and 39.7%of the tree species.Evergreen species or decreasing shade tolerance resulted in larger inflection points.The trends in the estimated inflection points of HOS and VBR were entirely opposite across the landscape.Furthermore,HOS could produce concave H-D curves for portions of the landscape.Based on the studied behaviors,the choice between two-parameter models may not matter.We recommend comparing seve ral three-parameter model forms for consistency in estimated inflection points before deciding on one.Believing sigmoidal models to have inflection points does not necessarily mean that they will produce fitted curves with one.Our study highlights the need to integrate analysis of inflection points into modeling H-D relationships.

Dominant woody plant species recognition with a hierarchical model based on multimodal geospatial data for subtropical forests

Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.

Generalized Height-Diameter Models for Pinus montezumae Lamb. and Pinus pseudostrobus Lindl. Plantations in Michoacan, Mexico

Tree height (H) in a natural stand or forest plantation is a fundamental variable in management, and the use of mathematical expressions that estimate H as a function of diameter at breast height (d) or variables at the stand level is a valuable support tool in forest inventories. The objective was to fit and propose a generalized H-d model for Pinus montezumae and Pinus pseudostrobus established in forest plantations of Nuevo San Juan Parangaricutiro, Michoacan, Mexico. Using nonlinear least squares (NLS), 10 generalized H-d models were fitted to 883 and 1226 pairs of H-d data from Pinus montezumae and Pinus pseudostrobus, respectively. The best model was refitted with the maximum likelihood mixed effects model (MEM) approach by including the site as a classification variable and a known variance structure. The Wang and Tang equation was selected as the best model with NLS;the MEM with an additive effect on two of its parameters and an exponential variance function improved the fit statistics for Pinus montezumae and Pinus pseudostrobus, respectively. The model validation showed equality of means among the estimates for both species and an independent subsample. The calibration of the MEM at the plot level was efficient and might increase the applicability of these results. The inclusion of dominant height in the MEM approach helped to reduce bias in the estimates and also to better explain the variability among plots.

Comparative research on three-echelon and two-echelon medicine inventory model with positive lead-time

According to the principle of minimizing total cost, the three-echelon optimized medical inventory model with stochastic lead-time and two-echelon optimized medicine inventory model with fixed lead-time are established. The relationship between lead-time and inventory cost is studied by Matlab software. It shows that the variety of lead-time has an important effect on medicine inventory systems. Numerical simulation and sensitivity analysis of two models are presented by Lingo software. Based on analysis, it is concluded that the two-echelon model with lead-time results in inventory cost savings, and keeps the quality of care as reflected in service levels when compared with the three-echelon network structure.

Infinitesimal dividing modeling method for dual suppliers inventory model with random lead times

As one of the basic inventory cost models, the （Q, τ）inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of ＂effective lead time＂ and ＂lead time demand＂, which may lead to an imprecise inventory cost. Through the real-time statistic of the inventory quantities, this paper considers the precise （Q, τ） inventory cost model of dual supplier procurement by using an infinitesimal dividing method. The traditional modeling method of the inventory cost for dual supplier procurement includes complex procedures. To reduce the complexity effectively, the presented method investigates the statistics properties in real-time of the inventory quantities with the application of the infinitesimal dividing method. It is proved that the optimal holding and shortage costs of dual supplier procurement are less than those of single supplier procurement respectively. With the assumption that both suppliers have the same distribution of lead times, the convexity of the cost function per unit time is proved. So the optimal solution can be easily obtained by applying the classical convex optimization methods. The numerical examples are given to verify the main conclusions.

Multi-objective linear fractional inventory model with possibility and necessity constraints under generalised intuitionistic fuzzy set environment

This study presented a multi-objective linear fractional inventory (LFI) problem with generalised intuitionistic fuzzy numbers. In modelling, the authors have assumed the ambiances where generalised trapezoidal intuitionistic fuzzy numbers (GTIFNs) used to handle the uncertain information in the data. Then, the given multi-objective generalised intuitionistic fuzzy LFI model was transformed into its equivalent deterministic linear fractional programming problem by employing the possibility and necessity measures. Finally, the applicability of the model is demonstrated with a numerical example and the sensitivity analysis under several parameters is investigated to explore the study.

Inventory Model with Supply Disruption Risk and Service Level Constraint

We develop a newsvender model with service level constraint for oneproduct and multi-supplier system, where the supplies are susceptible to disruption risks. We prove the convexity of the programming problem,and provide the necessary and sufficient conditions for the optimal order quantities. Through analysis or numerical experiments we observe the effects of the disrupt risk and the service level constraint on the optimal policy. We propose some managerial insights in managing the multi-source supply chain with disruption risks.

Research on Three-Echelon Inventory Model and Algorithm for Valuable Spare Parts in Weapon Equipment

According to the current situation of repair and supply for valuable spare parts in the weapon equipment of the PLA,using the research results of the repairable spare parts inventory theory,an inventory model of the valuable spare parts in three-echelon repair and supply system is established by expanding the classical METRIC model and theory,and the genetic algorithm is utilized to solve the model.In the algorithm,the chromosome representation and initial population production,the crossover and mutation operators are designed.By using an example,a simulation analysis is carried out to verify the model's correctness.

Mathematical Modelling for a Multi-Product Inventory Routing Problem with Split Delivery

In this article, a multi-product inventory routing problem is studied. One-depot and many retailers in a finite time period are considered, and split delivery is allowed as well for the addressed problem. The objective is to minimize the overall cost including vehicle cost, inventory holding cost and transportation cost while the delivery schedule and the quantity of each product for each retailer have to be decided simultaneously. A mathematical model is presented for solving the addressed optimally and example is illustrated as well.

Impact of Capacity Parameters on Flexible Inventory Control Decision Model

From the mathematical point of view,the flexible inventory control model is proved in the practical problem application and the rationality of the capacity parameter selection and calculation.The purpose is to actively respond to demand fluctuations when there is a demand forecast error or a missing part of the demand information,and to avoid the risk of passive variable demand forecasting to set the immutable inventory capacity.At the same time,the game is controlled by the flexible and variable inventory control strategy and the customer’s willingness to demand.The paper mainly studies the influence of the setting of capacity parameters on the booking-limit decision and its benefits under the control of flexible space with variable total capacity.Through the two trends of capacity increase flexibility and capacity reduction flexibility in the flexible inventory control model,the mathematical performance and marginal utility methods are introduced to change the performance of the booking-limit control decision model under different scenarios.The correlation analysis between the capacity limit level and the return under the optimal Bookinglimit decision,and the above two flexibility parameters are obtained.

Multi-Item Fuzzy Inventory Model Involving Three Constraints: A Karush-Kuhn-Tucker Conditions Approach

In this paper, a multi-item inventory model with storage space, number of orders and production cost as constraints are developed in both crisp and fuzzy environment. In most of the real world situations the cost parameters, the objective functions and constraints of the decision makers are imprecise in nature. This model is solved with shortages and the unit cost dependent demand is assumed. Hence the cost parameters are imposed here in fuzzy environment. This model has been solved by Kuhn-Tucker conditions method. The results for the model without shortages are obtained as a particular case. The model is illustrated with numerical example.

Field-Based Automated Survey for Extracting Tree Inventory Attributes and 3-D Models in a Forested Area

Acquisition of tree inventory parameters such as tree position with respect to a local reference coordinate system, tree height, dbh （diameter breast height） and other associated tree attributes is a tedious process, time consuming, costly and labour intensive. An automatic collection and processing in the field could expedite the process of tree inventory survey and data management. The advent of handheld laser equipments such as the MDL LaserAce 300, should allow rapid acquisition of tree attributes. The instrument measures distances, differences in height and horizontal bearing automatically. This paper describes a study about the automated process of retrieving tree positions, their respective attributes and the creation of 3-D model （three-dimensional model）. A software developed in-house known as ASSIST （automated spatial survey information system） was utilized together with the MI）I, LaserAce 300, being the hardware component of the automated system. The capability of MDL LaserAce 9300 in extracting information regarding tree inventory attributes and the 3-D model encompassing the study area was investigated. The results were checked against the data sets acquired by a total station traversing and tacheometric survey respectively. The accuracy of the horizontal and vertical position of points gathered was critically assessed. The accuracy of the MDL LaserAce 300 was found to be less than ±2 m for both planimetric （horizontal） and vertical （height） in the construction of the 3-D model. The study demonstrates the effectiveness of a field-based automation system as a viable option to support forest application requirement.

Optimization Model for School Transportation Based on Supply-Demand Analyses

This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport system. For this purpose, a mathematical equation was elaborated to simulate the real system based on the school transport conditions and on the estimated results of STSDR from 15 zones of Cuenca city in Ecuador. The data used in our model was collected from several diverse sources (i.e. administrative data and survey data). The estimated results have shown that our equation has described efficiently the school transport system by reaching an accuracy of 96%. Therefore, our model is suitable for statistical estimation given adequate data and will be useful in school transport planning policy. Given that, it is a support model for making decisions which seek efficiency in supply and demand balance.

An Improved Inventory Coordination Model in a Multi-stage Multi-customer Supply Chain

To solve the inventory coordination model in a multi-stage, multi-customer supply chain, this paper first analyzes the third model （integer powers of two multipliers at each firm） studied by Moutaz Khouja （2003）, and the authors take a numerical example to prove that the third model is irrational to miss feasible solution. Then this paper puts up a new improved model （integer multiplier at each firm）, and takes the example to prove it gives better results than the integer powers of two multipliers at each firm.

基于森林资源清查资料的盈江县森林生物量和生长量分析

为确定盈江县森林碳储量和碳汇潜力的变化特征及其影响因子,以便更好地分析盈江县森林生物量和生长量。基于盈江县2012年和2017年森林资源清查数据,利用生物量换算因子连续函数法和异速生长方程,评估盈江县森林碳储量和碳汇潜力的变化特征及其影响因子。结果显示:(1)盈江县森林生物量储量丰富,达85.55 t/hm^(2)。其中:栎类林最大,为168.3 t/hm^(2);核桃林最低,为7.10 t/hm^(2)。(2)不同林龄林分生物量差异较大,近熟林最高,其次分别为中龄林、成熟林、过熟林、幼龄林。(3)常绿阔叶林的林分生长量最大,其次是落叶阔叶林和针叶林。结果表明:盈江县森林生物量储量丰富且以阔叶林为主;林龄和年均气温是影响林分生长和生物量的主要因素。

基于MVC模式的医疗耗材管理系统设计

在医疗耗材管理中,整体管理方式比较滞后,造成大量耗材的浪费,为此,设计基于模型-视图-控制器(Model View Controller,MVC)模式的医疗耗材管理系统。基于MVC模式设计系统架构中的表现层。在系统硬件设计中,设计一种低功耗的处理器,由处理器芯片与电源管理单元构成。选用ASD-23型号的RFID节点,设计RFID阅读器。在系统软件设计中,设计档案管理单元、订单管理单元、查询统计单元构成管理模块,执行耗材管理的各种功能。设计供货商数据表、耗材数据表、入库表、供货商证照表等构成数据库模块。实验表明设计系统有着良好的健壮性、实时性、稳定性。

基于EOQ模型传统涉外制造企业物料库存管理研究

库存成本管理水平高低对企业经营成本有着直接影响,提高库存管理水平,有助于降低库存成本和经营成本。文章基于EOQ模型,以传统涉外制造企业DJ公司为例,选取物料面浆作为研究对象,通过对EOQ模型使用前后库存成本对比分析,发现采用EOQ模型后,面浆的库存量和库存总成本比原来有所降低。研究表明,科学合理采用EOQ模型有助于实现订货成本与维持成本最小化,降低企业经营成本,促进企业可持续发展。

昆明市高速公路机动车温室气体排放清单及时空性分布特征

为研究昆明市高速公路机动车的CO、CO_(2)、N_(2)O、CH_(4)温室气体排放清单,使用2021年昆明市高速公路客车交通流量数据、机动车GPS信息数据获得了高速公路网上的车型构成、车流量等基础数据,应用本土化修正后MOVES模型计算了昆明市高速公路的机动车CO、CO_(2)、N_(2)O、CH_(4)排放因子。基于实际交通流量数据、温室气体排放因子和昆明市高速公路实际道路信息,构建了昆明市高速公路机动车温室气体排放清单,并对其排放特征以及空间分布特征进行分析。结果表明:昆明市2021年高速公路机动车CO、CO_(2)、N_(2)O和CH_(4)的排放量分别为20337.1、2575677.1、33.8和72.9 t,总计CO_(2)当量为2626212.5 t。按排放标准划分,国Ⅳ排放标准的机动车是4种温室气体排放的主要贡献车型;按车辆类型划分,小型客车是CO、CO_(2)、N_(2)O排放的主要贡献车型,大型客车是CH_(4)排放的主要贡献车型;按燃料类型划分,汽油车是CO、CO_(2)、N_(2)O的主要贡献车型,柴油车是CH_(4)排放的主要贡献车型。昆明市高速公路机动车温室气体排放时间分布特征为排放强度与不同时间段的交通流量呈正相关,在24 h内呈现双高峰变化;空间分布特征为排放强度与路网密度和区域交通流量密切相关,路网密度较高和交通流量较高的区域排放强度较高。

黄河流域水环境问题研究现状、挑战与展望

黄河流域生态保护和高质量发展是国家重大发展战略,保护黄河是事关中华民族伟大复兴和永续发展的千秋大计.近年来,黄河流域水环境质量明显改善,但有限的水资源和脆弱的生态系统使得黄河流域水环境保护仍面临巨大的挑战.科学诊断黄河流域重大水环境问题是新时期治理黄河的前提和关键.本文围绕黄河流域水环境问题诊断这一主题,聚焦黄河流域断面水质改善的核心需求,首先分析黄河流域水环境现状,发现黄河流域整体水质持续向好,但干支流水质改善不同步,流域主要污染指标时空差异显著,中下游和部分支流污染严重;其次梳理国内外相关研究进展和主要挑战,总结断面水质提升所需的核心理论与技术,如水环境承载力评价、污染排放清单构建与水环境模型模拟等方面的应用与发展趋势,发现黄河流域存在气候变化影响下水沙变化大、现有排放清单分辨率不足、水环境模拟缺乏多尺度污染排放-断面水质响应关系研究等问题,难以支撑未来精细化水环境管理.对黄河流域水环境研究的未来发展进行了展望,建议未来在以下几个方面开展进一步研究,包括气候变化下黄河流域水环境承载力研究、黄河流域高分辨率排放清单构建、多尺度污染排放与断面水质响应关系.

考虑库存风险的服装行业新产品预售策略博弈研究

电子商务时代,服装行业线上销售的退货率居高不下。为缓解高退货率连带的库存风险,部分服装企业采用超长预售策略,在相对较长的预售期内次第发货满足顾客订单。在此现实背景下,文章基于报童模型,探讨商家在正常预售和超长预售中的策略选择,并求解两种策略的最优定价、产量、利润和可行条件。结果表明:当需求不确定性较大且产品残值较小,预售时长在合理的范围内且顾客更愿意等待时,应选择超长预售策略,反之选择正常预售策略;并且,超长预售策略能够显著降低库存剩余风险。研究结论对服装企业的预售决策和库存管理具有一定的现实参考价值。