Thesis (M.P.H.)--Southern Connecticut State University, 2006. / Page(s) missing in number only; text follows. Page(s) were scanned as received. Adviser: Sandra Bulmer. Includes bibliographical references.

Thesis (PhD) -- AUT University, 2008. / Includes bibliographical references. Also held in print (viii, 133 leaves : ill. ; 30 cm.) in the Archive at the City Campus (T 629.892 WON)

在建築物應急疏散過程中，人員個體的路徑選擇將影響人群整體的疏散情況。空間認知研究表明，人們通過認知獲取空間知識，並在認知地圖的指引下完成尋徑任務，尋徑過程因人而異。應急疏散時，建築物內部空間時有變化，心理壓力和人群活動等都將影響人員的路徑選擇。然而，現有疏散模型通常採用路徑搜索演算法來類比人員的逃生路徑。該方法多以最優路徑為目標，難以類比真實的尋徑過程，不能反映個體間的尋徑差異。因此，準確模擬人員個體的尋徑行為是建築物疏散模擬的研究重點。通過類比不同人群的疏散情況，採取針對性的疏散引導，可以有效緩解擁堵，提高疏散效率。 / 鑒於以上背景，本文以模擬多層建築中不同人群的疏散情況為目標，基於尋徑行為理論，考慮人群活動和室內空間變化的影響，分析建築物疏散時各類人員的尋徑行為，從而構建基於認知智慧體的疏散模型，類比多層建築的人員疏散。研究從以下方面展開： / （1）研究尋徑行為理論，分析建築物疏散時人員尋徑的知識需求和尋徑策略，考慮人群活動對個體尋徑的影響，構建建築物應急疏散時人員尋徑的過程模型。 / （2）研究建築物內部空間的表達方法，提出針對人群疏散類比的建築物空間表達模型。該模型在宏觀上採用基於語義的方法構建了的考慮消防設施的動態空間拓撲結構，在微觀上採用網格模型表達建築物內部幾何空間。 / （3）基於尋徑過程模型和建築物空間表達模型，構建基於認知智慧體的建築物疏散模型。智慧體行為模型以尋徑過程模型為理論基礎，包括知識表達，尋徑模型，環境認知模型和运動模型。 / （4）以某大學教學樓為例，驗證模型的可行性。考慮日常教學和籌辦會議等典型情況下的人群構成，模擬各個人群在不同火災場景下的疏散過程。通過對比出口使用率，分析不同人群的疏散差異。 / 研究結果表明，本文構建的建築應急物疏散模型能夠類比多層建築中各類人員的尋徑行為，反應不同人群的疏散差異，模擬結果更為合理，可以有效輔助人群疏散管理。 / In building evacuation, escape route choice of individual evacuees will potentially affect the overall evacuation performance. Studies in spatial cognition suggest that people find their ways based on spatial knowledge developed from environmental perception. Therefore, people with different level of spatial knowledge may vary tremendously in wayfinding performance. In the emergency situation, the building’s internal structure may change as some built-in facilities are activated. In the meantime, people’s psychic stress and crowd dynamics will significantly affect evacuees’ route selection. However, in most evacuation models, evacuees are simulated as particles that automatically follow the optimal escape route, and consequently without taking into account individual differences in wayfinding. Therefore, modelling individualized wayfinding is a critical issue in building evacuation simulation. It is expected that evacuation simulations regarding different types of evacuees would benefit the evacuation management targeted at a particular group of people. / Given the aforementioned background, the goal of this research is to model evacuees’ route choice in a plausible way by taking into account the cognitive process of human wayfinding and hereby perform evacuation simulations of different groups of evacuees in a multi-level building. In order to reach this goal, the following studies have been conducted: / (1) Based on literature studies on human wayfinding, a process model of wayfinding has been established. With regard to the emergency situation of building evacuation, typical wayfinding tasks, knowledge requirement, individual wayfinding strategies and influence of surrounding crowds are elaborated and incorporated into the process model. / (2) A novel approach to represent the dynamic spatial environments is developed to facilitate the evacuation simulation of multi-level buildings. At the macro level, a semantics-based model is established to represent the topological structure of building interiors which can be timely updated according to the status of fire safety facilities during emergency evacuation. At the micro level, a grid graph-based model is adopted to represent the geometry of building layout in order to facilitate the simulation of two-dimensional human movement. / (3) On the basis of the process model of wayfinding and the representation of dynamic spatial environment of building interiors, a computational model is developed using cognizing agent for building evacuation simulation. The architecture of the cognizing agent consists of knowledge representation, wayfinding model, environmental perception model and local movement model. / (4) The proposed model is verified and applied for the evacuation simulation of a university building. A series of evacuation simulations have been conducted in different fire scenarios with respect to the particular groups of evacuees in school days and conference days. Based on statistical analyses of exit utilization, evacuation performance of different groups of evacuees has been discussed and compared. / It has been proven that the proposed evacuation model, which incorporates the cognitive perspectives of human wayfinding, is capable of simulating a variety of route choice of different types of evacuees during the evacuation of a multi-level building. The model can be used to simulate the evacuation of different groups of evacuees, and thus provide more realistic basis for building evacuation management. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Tan, Lu. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 137-148). / Abstracts also in Chinese.

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xx, 182 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Jack L. Nasar, City and Regional Planning Dept. Includes bibliographical references (p. 121-135).

No description available.

Fuzzy Cognitive Maps (FCMs) are a widely used, neuro-fuzzy based qualitative approach for the modeling of dynamic systems, which allow for both static and dynamic analyses. They are capable of modeling complex systems with nonlinearities and unknown physical behaviour. FCMs describe a given system by means of concepts connected by quantified cause-effect relationships. This dissertation contributes to the subject of computer-driven generation of FCMs that can be used to perform an accurate dynamic analysis of the modeled system. The dynamic analysis provides insights into the degree of presence, and dependencies between the concepts in successive iterations of the simulation of a given FCM model. Such simulation studies could be used to analyze what-if scenarios in the context of decision support and to perform time series predictions. Two research directions within the framework of FCM development, which concern the learning of FCMs from historical data and an aggregation of FCMs that were proposed by multiple experts, are investigated. Several new automated computational methods for data-driven learning and aggregation of FCMs are introduced and empirically evaluated. These methods utilize real-coded genetic algorithms (RCGA)-based optimization. This choice of the optimization vehicle was motivated by their well-documented efficiency in searching large and continuous search spaces, which are inherent to our problem. Experimental evaluation demonstrates that the proposed RCGA-based learning method outperforms modern existing approaches when the dynamic analysis is considered. A novel divide and conquer-based learning strategy to improve scalability of the RCGA approach, is also proposed. This strategy is shown to be competitive or even better than solutions based on the parallelization of the underlying genetic algorithm. The RCGA-based learning method is further extended to provide improved FCMs when the number of connections of the map is known a priori. Experimental evaluation shows that the density-based learning method outperforms the generic RCGA-based approach when using a relatively accurate density estimate, and that both methods are equivalent when the estimate is inaccurate. In addition, a novel method for the aggregation of multiple input FCMs, is proposed. When compared to existing aggregation approaches, this method provides solutions that are more accurate when dynamic analysis is the objective. / Software Engineering and Intelligent Systems

Thesis (M.A.)--University of Oregon, 2008. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 88-91). Also available online.

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains vi, 85 p. : ill. (some col.), col. map. Includes abstract. Includes bibliographical references (p. 76-81).

No description available.

After the Second World War, there was an expression of interest in the study of the future. In order to achieve reliable objectives, several methods of scenario planning were invented. These methods comprise of qualitative and quantitative approaches inherited from their own school of origin. Each approach has advantages and limitations that can be observed by the study of each method in progress. However, mixed approaches often show a weak connection between qualitative and quantitative methods. The use of fuzzy cognitive maps (FCMs), among scenario planning approaches, can overcoming the limitations of qualitative and quantitative techniques. This study focused on the problem of the lack of proper planning of scenarios based on FCMs in the alternative energy sectors, raising the question of whether this situation comes from a shortage of information or limitations of the FCMs. To resolve this problem, this study investigated benefits and limitations of FCM-based scenario planning through the application in the Brazilian photovoltaic sector. The following specific objectives were established: identify the strong and weak points of FCMs; analyze the expansion of these to different areas; identification of the main stakeholders used to develop FCM-based scenarios; application of the method in the Brazilian solar energy sector. We identified an increasing number of studies on FCMs in several new areas not considered in previous studies. This suggests that experts are expanding frontiers and recognizing the interdisciplinary potential of FCMs and their robustness of solving diverse kinds of problems. The main contribution of the research is to present the benefits and limitations of FCM-based scenario planning. For that, a scenario planning method was presented and the empirical evidence of its effectiveness was presented in the context of the Brazilian photovoltaic solar energy sector. / Após a Segunda Guerra Mundial, houve um crescente de interesse no estudo do futuro. Para alcançar objetivos confiáveis, foram inventados vários métodos de planejamento de cenários. Esses métodos possuem abordagens qualitativas e quantitativas herdadas de sua própria escola de origem. Cada abordagem possui vantagens e limitações que podem ser observadas pelo estudo de cada método. No entanto, abordagens mistas muitas vezes mostram uma conexão fraca entre métodos qualitativos e quantitativos. O uso de fuzzycognitivemaps (FCMs), no planejamento de cenários, pode superar as limitações das técnicas qualitativas e quantitativas. Este estudo centrou-se no problema da falta de planejamento adequado de cenários baseados em FCMs nos setores de energia alternativa, levantando a questão de saber se esta situação vem da escassez de informações ou das limitações dos FCMs no planejamento estratégico. Para resolver este problema, este estudo investigou os benefícios e as limitações do planejamento de cenários baseado em FCM através da aplicação no setor fotovoltaico brasileiro. Foram estabelecidos os seguintes objetivos específicos: identificar os pontos fortes e fracos dos FCMs; analisar a expansão destes para diferentes áreas; identificar os principais stakeholders utilizados para desenvolver cenários baseados em FCMs; aplicar o método no setor de energia solar brasileira. Identificamos um número crescente de estudos sobre FCMs em várias novas áreas não consideradas em estudos anteriores. Isso sugere que os especialistas estão expandindo as fronteiras e reconhecendo o potencial interdisciplinar dos FCMs e sua robustez na resolução de diversos tipos de problemas. A principal contribuição desta pesquisa é apresentar os benefícios e as limitações do planejamento de cenário baseado em FCM. Para isso, foi apresentado um método de planejamento de cenários e a evidência empírica de sua eficácia foi apresentada no contexto do setor de energia solar fotovoltaica brasileira.