治污投资的政府最优政策博弈

外部性的存在及制造商治污投资动机不足要求政府对制造商的行为进行相应的规制，政府在制造商的治污投资行为中主要的作用是通过各种措施使得制造裔有动机地去自觉地进行有效的治污投资;政府的主要控制手段包括直接管制及借助市场激励，政府制定环境管理策略的关键因素是“惩罚的力度与激励的强度”。基于社会福利最大化的角度；从制造商的治污投资行为出发研究政府制定环境管理规制的策略，通过一个三阶段的博弈模型分析福利增进量、洽污成本与治污效果等三个因素对“惩罚力度与激励强度”的影响。     

乡村振兴视域下农村土地利用利益相关者分析

乡村振兴的实施使得农村土地利用与管理面临更多的挑战。应用利益相关者分析、博弈均衡分析和实证案例分析,探讨乡村振兴视域下土地利用各利益相关者的关系演变。研究结果显示：（1）1949年至今,农村地区土地利用利益相关者主体数量增加,博弈关系呈现复杂化、多样化和多向化;（2）乡村振兴时期主要有六种博弈关系,并探讨了案例村实施下山脱贫、发展乡村旅游、新型经营主体进驻、城市居民促进农村发展四种博弈决策过程;（3）乡村振兴视域下,农村地区发展应关注基础设施配套、土地利用效率与生态环境协调、农户生计可持续性等问题。乡村振兴中应注重实现土地利用各利益相关者的最优均衡,降低各方风险,保护生态环境并寻求多方利益平衡。     

Game theory approach to optimal capital cost allocation in pollution control

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博弈理论在公众聚集场所消防监督管理的应用

建立了公安消防部门和公众聚集场所之间的公共安全管理模型.通过分析该模型,确定公安消防部门对公众聚集场所进行抽检的比例,对公众聚集场所不安全营业的处罚力度,以及抽检比例与处罚力度之间的函数关系.     

Sustainability and comanagement of subsistence hunting in an indigenous reserve in Guyana

Although hunting is a key component of subsistence strategies of many Amazonians, it is also one of the greatest threats to wildlife. Because indigenous reserves comprise over 20% of Amazonia, effective conservation often requires that conservation professionals work closely with indigenous groups to manage resource use. We used hunter‐generated harvesting data in spatially explicit biodemographic models to assess the sustainability of subsistence hunting of indigenous Waiwai in Guyana. We collected data through a hunter self‐monitoring program, systematic follows of hunters, and semistructured interviews. We used these data to predict future densities of 2 indicator species, spider monkeys (Ateles paniscus) and bearded sakis (Chiropotes sagulatus), under different scenarios of human population expansion and changing hunting technology. We used encounter rates from transect surveys and hunter catch‐per‐unit effort (CPUE) to validate model predictions. Paca (Cuniculus paca) (198 /year), Currosaw (Crax alector) (168), and spider monkey (117) were the most frequently harvested species. Predicted densities of spider monkeys were statistically indistinguishable from empirically derived transect data (Kolmogorov–Smirnov D = 0.67, p = 0.759) and CPUE (D = 0.32, p = 1.000), demonstrating the robustness of model predictions. Ateles paniscus and C. sagulatus were predicted to be extirpated from <13% of the Waiwai reserve in 20 years, even under the most intensive hunting scenarios. Our results suggest Waiwai hunting is currently sustainable, primarily due to their low population density and use of bow and arrow. Continual monitoring is necessary, however, particularly if human population increases are accompanied by a switch to shotgun‐only hunting. We suggest that hunter self‐monitoring and biodemographic modeling can be used effectively in a comanagement approach in which indigenous parabiologists continuously provide hunting data that is then used to update model parameters and validate model predictions.     

博弈论在弹道导弹核潜艇威慑能力定性评估中的应用

以国际政治经济学领域常用的博弈论为基础,建立了不同情况下的弹道导弹核潜艇核威慑能力的定性分析模型,其核心是分析威慑双方的策略互动,以便能够更加客观地对弹道导弹核潜艇的威慑能力进行评估。针对信息完全和信息缺失的情况,博弈论模型能够简便快捷地对弹道导弹核潜艇的核威慑效果进行评估,并能够提出提高潜艇威慑效果的具体措施。     

企业安全投资背后的利益博弈探讨

利用职业安全卫生费用模型结合博弈论原理,对企业安全投资背后的利益冲突与协调问题进行了浅析.研究表明:企业凭借资本优势在与政府和劳动者的利益博弈中为了寻求经济利益最大化减少安全投资,使企业安全度大大降低,导致事故频发是政府、企业和劳动者之间利益博弈的结果.此外,劳动者的合法权益得不到保护,造成其在利益博弈中处于弱势地位是造成安全生产现状的重要原因之一.     

生态恢复过程中的种群遗传学考虑

生态恢复是生态科学的最终实验,从种群角度看,恢复的目标是使种群（尤其是优势种或建群种）到具有生长、繁殖和适应进化变化的能力。要达到这个目标,种群遗传学知识必不可少。遗传变异是物种适应变化环境的基础,而局部适应则是种群适应局部环境遗传分化的结果,它们在生态恢复中起着重要的作用。分析了生态恢复过程中影响种群遗传变异因素,主要有取样误差和小种群效应（主要是瓶颈或建立者事件及其以后的近交和漂变等）,在进行     

A conceptual approach to model sand–gravel extraction from rivers based on a game theory perspective

Sand–gravel mining is a significant parameter of economic development and social welfare function in modern societies. As demand for aggregate increases in construction industry, conflicts for the availability of the resource and environmental impacts become more intense. The present paper describes the contested status quo in riverbed sand–gravel mining activities with an example from Greece, as a case study. The scope is to propose a methodology about good governance of the mining sector that promotes a sustainable sharing of aggregate resource by securing environment and safekeeping revenues in the mining trade market.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.