Rationale for Decision-Making Processes in Enhancement of Community Participation for Sustainable Mangrove Management in Lamu, Kenya

Decision-making is the process of deciding between two or more options in order to take the most appropriate and successful course of action in order to achieve sustainable mangrove management. However, the distinctiveness of mangrove as an ecosystem, and thus the attendant socio-economic and governance ramifications, causes the idea of decision making to become relatively distinct from other decision making process As a result, the purpose of this research was to evaluate the impact that community engagement plays in the decision-making process as it relates to the establishment of governance norms for sustainable mangrove management in Lamu County. In this study, a correlational research design was applied, and the researchers employed a mixed techniques approach. The target population was 296 respondents. The research used questionnaires and interviews to collect data. A descriptive statistical technique was utilized to perform an inspection and analysis on the data that was gathered. The findings indicated that having awareness about governance standards is beneficial during the process of making decisions. In addition, the findings demonstrated that respondents had the impression that the decision-making process was not done properly. On the other hand, the participants pointed out the positive aspects of the decision-making process and agreed that the participation of both gender was essential for the sustainable management of mangroves. Based on these data, it appeared that full community engagement in decision-making is necessary for sustainable management of mangrove forests.

A Comparative Analysis of Visualization Methods in Architecture:Employing Virtual Reality to Support the Decision-Making Process in the Architecture,Engineering,and Construction Industry

The design process of the built environment relies on the collaborative effort of all parties involved in the project.During the design phase,owners,end users,and their representatives are expected to make the most critical design and budgetary decisions-shaping the essential traits of the project,hence emerge the need and necessity to create and integrate mechanisms to support the decision-making process.Design decisions should not be based on assumptions,past experiences,or imagination.An example of the numerous problems that are a result of uninformed design decisions is“change orders”,known as the deviation from the original scope of work,which leads to an increase of the overall cost,and changes to the construction schedule of the project.The long-term aim of this inquiry is to understand the user’s behavior,and establish evidence-based control measures,which are actions and processes that can be implemented in practice to decrease the volume and frequency of the occurrence of change orders.The current study developed a foundation for further examination by proposing potential control measures,and testing their efficiency,such as integrating Virtual Reality(VR).The specific aim was to examine the effect of different visualization methods(i.e.,VR vs.construction drawings)on,(1)how well the subjects understand the information presented about the future/planned environment;(2)the subjects’perceived confidence in what the future environment will look like;(3)the likelihood of changing the built environment;(4)design review time;and(5)accuracy in reviewing and understanding the design.

COLLISION AVOIDANCE DECISION-MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

Process Auxiliary Decision-making Based on Rough Sets and Regulation Distance Computing

Computer aided process planning（CAPP） is an important content of computer integrated manufacturing, and intelligentizing is the orientation of development of CAPP. Process planning has characters of empirical and time-consuming to finalize, and the same technical aim always can be achieved by different process schemes, so intelligentizing of process decision making always be a difficult point of CAPP and computer integrated manufacturing （CIM）. For the purpose of intelligent aided process decision making and reuse of process resource, this paper proposed a decision making method based on rough sets（RS） and regular distance computing. The main contents and methods of process planning decision making are analyzed under agile response manufacturing environment, the concept of process knowledge granule is represented, and the methods of process knowledge granule partitioning and granularity analysis are put forward. Based on the theory of RS and combined the method of process attributes importance identification, the paper brought forward a computing model for process scheme regulation distance under the same attribute conditions, and conflict resolution strategy was introduced to acquire process scheme fit for actual situation of enterprise＇s manufacturing resources, so as to realize process resources＇ conflict resolution and quick excavate and reuse of enterprises＇ existing process knowledge, to advance measures of process decision making and improve the rationality and capability of agile response of process planning.

Analysis on decision-making model of plan evaluation based on grey relation projection and combination weight algorithm

In military service joint operations, when there are more operational forces, more multifarious materials are consumed, the support is more complex and fuzzy, the deployment of personnel is more rapid, and the support provided by wartime military material support powers can be more effective. When the principles,requirements, influencing factors and goals of military material support forces are deployed in wartime, an evaluation indicator system is established. Thus, a new combined empowerment method based on an analytic hierarchy process（AHP） is developed to calculate the subjective weights, and the rough entropy method is used to calculate the objective weights. Combination weights can be obtained by calculating the weight preference coefficient error, which is determined by combining the cooperative game method and the minimum deviation into objectives. This approach can determine the grey relation projection coefficient and synthesize the measure scheme superiority to finally optimize the deployment plan using the grey relation projection decision-making method. The results show that the method is feasible and effective;it can provide a more scientific and practical decision-making basis for the military material support power deployment in wartime.

Brain areas activated by uncertain reward-based decision-making in healthy volunteers

Reward-based decision-making has been found to activate several brain areas, including the ven- trolateral prefronta~ lobe, orbitofrontal cortex, anterior cingulate cortex, ventral striatum, and mesolimbic dopaminergic system. In this study, we observed brain areas activated under three de- grees of uncertainty in a reward-based decision-making task （certain, risky, and ambiguous）. The tasks were presented using a brain function audiovisual stimulation system. We conducted brain scans of 15 healthy volunteers using a 3.0T magnetic resonance scanner. We used SPM8 to ana- lyze the location and intensity of activation during the reward-based decision-making task, with re- spect to the three conditions. We found that the orbitofrontal cortex was activated in the certain reward condition, while the prefrontal cortex, precentral gyrus, occipital visual cortex, inferior parietal lobe, cerebellar posterior lobe, middle temporal gyrus, inferior temporal gyrus, limbic lobe, and midbrain were activated during the ＇risk＇ condition. The prefrontal cortex, temporal pole, inferior temporal gyrus, occipital visual cortex, and cerebellar posterior lobe were activated during am- biguous decision-making. The ventrolateral prefrontal lobe, frontal pole of the prefrontal lobe, orbi- tofrontal cortex, precentral gyrus, inferior temporal gyrus, fusiform gyrus, supramarginal gyrus, infe- rior parietal Iobule, and cerebellar posterior lobe exhibited greater activation in the ＇risk＇ than in the ＇certain＇ condition （P 〈 0.05）. The frontal pole and dorsolateral region of the prefrontal lobe, as well as the cerebellar posterior lobe, showed significantly greater activation in the ＇ambiguous＇ condition compared to the ＇risk＇ condition （P 〈 0.05）. The prefrontal lobe, occipital lobe, parietal lobe, temporal lobe, limbic lobe, midbrain, and posterior lobe of the cerebellum were activated during deci- sion-making about uncertain rewards. Thus, we observed different levels and regions of activation for different types of reward processing during decision-making. Specifically, when the degree of reward uncertainty increased, the number of activated brain areas increased, including greater ac- tivation of brain areas associated with loss.

Dual worth trade-off method and its application for solving multiple criteria decision making problems

To overcome the limitations of the traditional surrogate worth trade-off （SWT） method and solve the multiple criteria decision making problem more efficiently and interactively, a new method labeled dual worth tradeoff （DWT） method is proposed. The DWT method dynamically uses the duality theory related to the multiple criteria decision making problem and analytic hierarchy process technique to obtain the decision maker＇s solution preference information and finally find the satisfactory compromise solution of the decision maker. Through the interactive process between the analyst and the decision maker, trade-off information is solicited and treated properly, the representative subset of efficient solutions and the satisfactory solution to the problem are found. The implementation procedure for the DWT method is presented. The effectiveness and applicability of the DWT method are shown by a practical case study in the field of production scheduling.

A Quantity Model for Controlling and Measuring Software Quality Based on the Expert Decision-Making Algorithm

Researchers have been active in the field of software engineering measurement over more than 30 years. The software quality product is becoming increasingly important in the computerized society. Target setting in software quality function and usability deployment are essential since they are directly related to development of high quality products with high customer satisfaction. Software quality can be measured as the degree to which a particular software program complies with consumer demand regarding function and characteristics. Target setting is usually subjective in practice, which is unscientific. Therefore, this study proposes a quantity model for controlling and measuring software quality via the expert decision-making algorithm-based method for constructing an evaluation method can provide software in relation to users and purchasers, thus enabling administrators or decision makers to identify the most appropriate software quality. Importantly, the proposed model can provide s users and purchasers a reference material, making it highly applicable for academic and government purposes.

Factors Affecting Selection of Elective Courses:The Use of Multi-Criteria Decision Making Model

Elective course selection has always been a serious and important decision making process for students in institutions. The aim of this study is to determine weights of factors affecting elective course selection from students' perspective. So as to solve the problem, Analytic Hierarchy Process (AHP) based model was used. Factors which affect the elective course selection from students' point of view include five main criteria and 13 sub-criteria which were indicated by students. An online questionnaire containing demographic questions, enabled each student to compare the relative priority of criteria with all of the other criteria. The responses were evaluated via Super Decisions software, and priorities were determined using the Analytic Hierarchy Process (AHP). According to the analysis of 40 experts (i.e., graduate students studying in engineering programs), course schedule and teaching staff related factors are the two most important factors affecting the elective course selection. A real- life situation which will help students who are indecisive and hesitates while selecting an elective course was observed. AHP contributes to develop an analytic and comprehensive framework decision making. The method should be considered by faculty member involved in decisions about curriculum update and offering new courses.

A STUDY ON DECISION-MAKING OF ENVIRONMENTAL IMPACTS FOR REGIONAL WATER RESOURCES DEVELOPMENT

On the basis of overall analysis, this Paper, taking Beijing-Tianjin-Tangshan region as an example, tries to find out main environmental problems caused by water resources development and to discuss the mitigaive measures of the environmental impacts. The Paper, by means of Analytical Hierarchy Process (AHP, builds a multiple-hierarchy decision-making model including godl, water resources, environmental impact factors and mitigative measures. This study is very significant for alleviating and solving the problems of water resources-environmental system in the region.

Control Method of Effect of Robust Optimization in Multi-Player Multi-Objective Decision-Making

In the real situations of supply chain, there are different parts such as facilities, logistics warehouses and retail stores and they handle common kinds of products. In this research, these situations are focused on as the background of this research. They deal with the common quantities of their products, but due to their different environments, the optimal production quantity of one part can be unacceptable to another part and it may suffer a heavy loss. To avoid that kind of unacceptable situations, the common production quantities should be acceptable to all parts in one supply chain. Therefore, the motivation of this research is the necessity of the method to find the production quantities that make all decision makers acceptable is needed. However, it is difficult to find the production quantities that make all decision makers acceptable. Moreover, their acceptable ranges do not always have common ranges. In the decision making of car design, there are similar situations to this type of decision making. The performance of a car consists of purposes such as fuel efficiency, size and so on. Improving one purpose makes another worse and the relationship between these purposes is tradeoff. In these cases, Suriawase process is applied. This process consists of negotiations and reviews of the requirements of the purposes. In the step of negotiations, the requirements of the purposes are share among all decision makers and the solution that makes them as satisfied as possible. In the step of reviews of the requirements, they are reviewed based on the result of the negotiation if the result is unacceptable to some of decision makers. Therefore, through the iterations of the two steps, the solution that makes all decision makers satisfied is obtained. However, in the previous research, the effects that one decision maker reviews requirements in Suriawase process are quantified, but the mathematical model to modify the ranges of production quantities of all decision makers simultaneously is not shown. Therefore, in this research, based on Suriawase process, the mathematical model of multi-player multi-objective decision making is proposed. The mathematical model of multi-player multi-objective decision making by using linear physical programming (LPP) and robust optimization (RO) in the previous research is the basis of the methods of this research. LPP is one of the multi-objective optimization methods and RO is used to make the balance of the preference levels among decision makers. In LPP, the preference ranges of all objective functions are needed, so as the hypothesis of this research. In the research referred in this research, the method to control the effect of RO is not shown. If the effect of RO is too big, the average of the preference level becomes worse. The purpose of this research is to reproduce the mathematical model of multi-player multi-objective decision making based on Suriawase process and propose the method to control the effect of RO. In the proposed model, a set of the solutions of the negotiation problem is obtained and it is proved by the result of the numerical experiment. Therefore, the conclusion that the proposed model is available to obtain a set of the solutions of the negotiation problems in supply chain.

结合STPA和DEMATEL-ISM的民机起落架收放系统风险研究

为从系统整体角度完成对起落架收放系统的风险辨识和影响分析,将系统理论过程分析(Systematic Theory Process Analysis,STPA)与决策实验室分析-解释结构模型(Decision Making Trial and Evaluation Laboratory Interpretive Structural Modeling,DEMATEL-ISM)相结合来开展分析。首先,定义事故和系统级危险,以民机进近阶段放下起落架为例,运用STPA完成对风险因素的系统化辨识;其次,基于最大平均熵减(Maximum Mean De-entropy,MMDE)算法帮助DEMATEL-ISM模型确定阈值,完成对风险因素影响的重要性分析并识别可能引发系统级危险的风险传递路径,据此挖掘关键致因场景,以给出风险预防建议。结果显示:线路性能退化或失效、位置作动控制组件(Position Action Control Unit,PACU)核心处理器故障为关键原因因素,收放作动筒作动异常、机组成员操作不当、起落架指示灯显示异常、起落架液压选择阀作动异常、PACU信息接收有误为关键结果因素,这些因素均涉及多条可能引发系统级危险的风险传递路径,应予以重点控制。

An Interactive Expert System Based Decision Making Model for the Management of Transit System Alternate Fuel Vehicle Assets

Traditionally, the process used by public transportation entities to determine the acquisition strategy for new vehicle asset is based upon a broad range of criteria. Vehicle cost has been cited as one of the more critical factors which decision makers consider. It is currently a common practice to consider other factors (life-cycle cost, fuel efficiency, vehicle reliability, environmental effects, etc.) that contribute to a more comprehensive approach. This study investigates the next generation of advancements in decision making tools in the area of the application of methods to quantify and manage uncertainty. In particular, the uncertainty comes from the public policy arena where future policy and regulations are not always based upon logical and predictable processes. The fleet decision making process in most governmental agencies is a very complex and interdependent activity. There are always competing forces and agendas within the view of the decision maker. Rarely is the decision maker a single person although, within the transit environment, there is often one person charged with the responsibility of fleet management. The focus of this research examines the decision making of the general transit agency community via the development of an expert systems prototype tool. A computer-based prototype system is developed which provide an expert knowledge-based recommendation, based upon variable user inputs. The results shown in this study show that a decision making tool for the management of transit system alternate fuel vehicle assets can be modeled and tested. The direct users of this research are the transit agency administrations. The results can be used by the management teams as a reliable input to inform their urban transit buses expansion decision making process.

Integration of Decision-Support and Knowledge-Based Techniques in a Problem-Solving Strategy for Selection Problems

The limitations of traditional approaches to selection problems are examined. A problemsolving strategy is presented in which decision-support and knowledge-based techniques play complementary roles. An approach to the representation of knowledge to support the problem-solving strategy is presented which avoids commitment to a specific programming language or implementation environment. The problem of choosing a home is used to illustrate the representation of knowledge in a specific problem domain. Techniques for implementation of the problem-solving strategy are described. Knowledge elicitation techniques and their implementation in a development shell for application of the problem-solving strategy to any selection problem are also described.

基于改进STPA-DEMATEL的智能航电系统致因要素分析

针对智能航电系统在非线性耦合运行场景下产生的预期功能安全(safety of the intended functionality,SOTIF)问题,提出一种将系统理论过程分析(systematic theory process analysis,STPA)与决策试验与评价实验法(decision-making trial and evaluation laboratory,DEMATEL)相结合的致因分析框架。首先,在定义系统级危险的基础上构建安全控制结构,识别其不安全控制行为并提取与智能化缺陷相关的STPA致因要素。接下来,引入毕达哥拉斯模糊加权平均算子和闵可夫斯基距离对传统DEMATEL方法进行优化,专家根据控制反馈回路对致因要素进行评价并计算其中心度与原因度。最后,分析STPA致因要素与SOTIF致因属性之间的映射关系,给出关键致因要素的风险减缓措施。以单一飞行员驾驶(single-pilot operation,SPO)模式下的虚拟驾驶员助理系统为例说明了所提方法的可行性与有效性。研究结果表明,改进的STPA-DEMATEL方法可以有效识别关键致因要素,且能够克服专家评价的模糊性与不确定性,为智能航电系统的安全性设计提供了参考依据。

Using Mathematical Models in Decision Making Methodologies to Find Key Nodes in the Noordin Dark Network

A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many measures and metrics. For each of these measures and metric, the output in ORA additionally provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning best methods to disrupt or deceive a given dark network. In the Noordin Dark network, different nodes were identified as key nodes based upon the metric used. Our goal in this paper is to use methodologies to identify the key players or nodes in a Dark Network in a similar manner as we previously proposed in social networks. We apply two multi-attribute decision making methods, a hybrid AHP & TOPSIS and an average weighted ranks scheme, to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs. We compare these methods by illustration using the Noordin Dark Network with seventy-nine nodes. We discuss sensitivity analysis that is applied to the criteria weights in order to measure the change in the ranking of the nodes.

基于AHP-DEMATEL的公路养护决策与计划实施后评估方法

针对当前中国在公路领域,尤其是公路养护领域后评价管理制度的缺失,该文提出一种基于层次分析法(AHP)与决策实验室分析法(DEMATEL)相结合的公路养护决策与计划实施后评估评价方法,建立公路养护决策与计划实施后评估模型,设计公路养护决策与计划实施后评估评价流程,计算出影响公路养护决策与计划实施后评估评价的关键因素和它们各自的综合权重。研究结果表明:结合公路养护决策与计划实施后的评估标准计算得到各级评估指标的综合权重,能够提高决策的精准性和效率,为项目计划的制定提供决策依据。

基于FAHP-灰色关联法的飞机结构修理方案选择

飞机结构修理对于保障飞机的安全运行具有重要意义,为从若干结构修理方案中选取最优方案,运用何种决策方法对决策有效性起着决定性作用。为避免维修飞机的数据缺失和信息掌握不完善等情况对决策的影响,将改进的模糊层次分析法与灰色关联法相结合,充分利用现有数据和专家意见进行飞机结构修理方案决策。首先运用改进的模糊层次分析法计算出各影响因素对方案层的权重,再结合灰色关联法计算方案层的关联度值并将结果进行排序,关联度最大的方案即为最佳修理方案。该方法对飞机结构的修理决策具有重要的指导意义和工程应用价值。

A Model-Based, Aspiration-Led Decision Support System NY-IEDSS

An AI-aided simulation system embedded in a model-based, aspiration-led decision support system NY-IEDSS is reported. The NY-IEDSS is designed for mid-term development strategic study of the Nanyang Region in Henan, China, and is getting beyond its prototype stage under the decision maker's (the end user) orientation. The integration of simulation model system, decision analysis and expert system for decision support in the system implementation was reviewed. The intent of the paper is to provide insight as to how system capability and acceptability can be enhanced by this integration. Moreover, emphasis is placed on problem orientation in applying the method.