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Wu, Jun. "An early warning system for currency crises /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?ECON%202007%20WU.
Повний текст джерелаJadi, Amr. "An early warning system for risk management." Thesis, De Montfort University, 2013. http://hdl.handle.net/2086/9659.
Повний текст джерелаBarbosa, Jorge Henrique de Frias. "Early Warning System para distress bancário no Brasil." reponame:Repositório Institucional da UnB, 2017. http://repositorio.unb.br/handle/10482/24912.
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Esta tese é composta por três artigos que cobrem tópicos sobre o tema de early warning system para crises bancárias e distress bancário: uma pesquisa bibliométrica sobre early warning system (EWS) para crises bancárias e distress, um estudo empírico que estima um early warning system para distress de bancos brasileiros com regressão logística e um estudo empírico que constrói um early warning system com técnicas de aprendizagem de máquina supervisionada. O primeiro artigo apresenta um panorama do estado da literatura sobre EWS para crises bancárias e distress bancário por meio de uma revisão bibliométrica da literatura apresentando as principais ideias, principais conceitos, principais relacionamentos com outros tipos de crises, principais métodos utilizados, principais indicadores de crises e de distress. Foi realizada uma pesquisa em nas bases da Scopus e da Web of Science, onde, a partir de critérios de seleção, foram encontrados 124 artigos que foram devidamente classificados e codificados mediante importantes critérios para a área de estudo. Foi apresentado a evolução dos estudos na área, as gerações e tipos de EWS e os principais indicadores micro e macroprudencias apresentados pelos estudos da amostra. Como um resultado das lacunas da literatura na área é proposta uma agenda estruturada, visando guiar novos estudos por meio da apresentação de lacunas com grande potencial para ser explorada e reforçar o estado da arte em EWS. Adicionalmente, os resultados demonstram que mais estudos são necessários em EWS com relação à determinação dos horizontes de tempo para as previsões do modelo, com relação a estudos que tratam da América do Sul, América Central e África. Futuros estudos também devem considerar a possibilidade de utilização de modelos de aprendizagem de máquina, inteligência artificial e métodos computacionais, pois ainda existem poucos estudos e os resultados são promissores. O segundo artigo contribuiu com algumas inovações, como a construção e utilização de uma nova base dados de eventos de distress de bancos brasileiros, incluindo 179 eventos considerados como distress bancário de acordo com a definição de ?, incluindo 8 casos de RAET, 9 casos de intervenção, um caso de PROER, 11 casos de privatizações, 32 casos de incorporação e fusão, 13 casos de transformação em outros tipos de instituições financeiras, 32 caso de transformação de bancos em outros tipos de instituições, 21 casos de cancelamento e 52 casos de liquidação extrajudicial. Foi construído um painel de dados a partir de 54.087 balancetes de 359 bancos, englobando o período de julho de 1994 a novembro de 2016, juntamente com dados do setor bancário brasileiro e dados macroeconômicos. Para tratar do problema de eventos raros. O presente estudo utilizou a abordagem SMOTE (Synthetic Minority Over-sampling Technique) que pode aumentar a performance do modelo em termos da área sob a curva ROC (Area under the Receiver Operating Characteristic curve - AUC), uma técnica que que maximiza a área sob a curva ROC (AUC - area under the curve). Outra contribuição do segundo estudo foia comparação de modelos de acordo com o horizonte de tempo das previsões, característica importante para um EWS. Verificou-se que o modelo com o horizonte de tempo de 6 meses foi o modelo com maior área sob a curva ROC, para os dados da amostra utilizada, considerando-se o período de julho de 1994 até novembro de 2016. No terceiro artigo, foram utilizadas duas técnicas de aprendizagem de máquina supervisionada para construir EWSs: random forest e SVM (support vector machines) que obtiveram resultados superiores ao modelo de regressão logística apresentado no segundo estudo. Ambos os modelos de aprendizagem de máquina superam a regressão logística, em termos de acurácia, área sob a curva AUC (Area Under the Curve –AUC), sensibilidade (valor preditivo positivo) e especificidade (valor preditivo negativo). E o modelo random forest também superou o SVM em termos de acurácia, área sob a curva (AUC), sensibilidade e especificidade. Verificou-se também que os modelos random forest apresentaram melhor qualidade de previsão com as janelas de tempo de 32 e 34 meses, mostrando-se adequados às necessidades das autoridades.
This thesis consistis of three articles covering topics in early warning system (EWS) for bank crises and distress: an empirical study that estimates an early warning system for distress of Brazilian banks with logistic regression and an empirical study that builds an early warning system with techniques Of supervised machine learning. The first article presents an overview of the literature on EWS for bank crises and bank distress through a bibliometric review of the literature presenting the main ideas, main concepts, main relationships with other types of crises, main methods used, main crisis indicators And distress. A survey was carried out in the databases of Scopus and the Web of Science, where, based on selection criteria, 124 articles were found that were duly classified and codified by important criteria for the study area. The evolution of the studies in the area, the generations and types of EWS and the main micro and macroprudential indicators presented by the sample studies were presented. As a result of the literature gaps in the area, a structured agenda is proposed, aimed at guiding new studies through the presentation of gaps with great potential to be explored and to reinforce the state of the art in EWS. In addition, the results demonstrate that more studies are needed in EWS regarding the determination of time horizons for model predictions, in relation to studies dealing with South America, Central America and Africa. Future studies should also consider the possibility of using machine learning models, artificial intelligence and computational methods, as there are still few studies and the results are promising. The article contributed some innovations such as the construction and use of a new database of distress events of Brazilian banks, including 179 events considered as bank distress according to the definition of ?, including 8 cases of RAET (Temporary Special Administration Scheme), 9 cases of intervention, one PROER (The Program of Incentives for the Restructuring and Strengthening of the National Financial System) case, 11 cases of privatization, 32 cases of incorporation and merger, 13 cases of transformation in other types of financial institutions, 32 cases of transformation of banks into other types of institutions, 21 cases of cancellation and 52 cases of extrajudicial liquidation. A data panel was constructed from 54,087 balance sheets of 359 banks, covering the period from July 1994 to November 2016, together with data from the Brazilian banking sector and macroeconomic data. In order to address the problem of rare events, the present study used the Synthetic Minority Over-sampling Technique (SMOTE) approach that can increase the model’s performance in terms of the Area under the Receiver Operating Characteristic curve (AUC), a technique that maximizes the area under the ROC curve (AUC). Another contribution of the second study was the comparison of models according to the time horizon of the forecasts, an important feature for an EWS. It was verified that the model with the time horizon of 6 months was the model with the largest area under the ROC curve, for the data of the sample used, considering the period from July 1994 to November 2016. In the third article, two supervised machine learning techniques were used to construct EWSs: random forest and SVM (support vector machines) that obtained results superior to the logistic regression model presented in the second study. Both models of machine learning outperform logistic regression in terms of accuracy, area under the AUC curve, sensitivity (positive predictive value) and specificity (negative predictive value). And the random forest model also surpassed the SVM in terms of accuracy, area under the curve (AUC), sensitivity and specificity. It was also verified that the random forest models presented better quality of prediction with the forecast time horizons of 32 and 34 months, being adapted to the needs of the authorities.
Black, Gary. "Pollution prevention in wastewater networks : development of a biological early warning device." Thesis, Cranfield University, 2016. http://dspace.lib.cranfield.ac.uk/handle/1826/10290.
Повний текст джерелаConner, Christine. "Evaluating the Impact of an Early Warning Scoring System in a Community Hospital Setting." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/4846.
Повний текст джерелаCeolin, Junior Tarcisio. "CORRELAÇÃO DE ALERTAS EM UM INTERNET EARLY WARNING SYSTEM." Universidade Federal de Santa Maria, 2014. http://repositorio.ufsm.br/handle/1/5439.
Повний текст джерелаIntrusion Detection Systems (IDS) are designed to monitor the computer network infrastructure against possible attacks by generating security alerts. With the increase of components connected to computer networks, traditional IDS are not capable of effectively detecting malicious attacks. This occurs either by the distributed amount of data that traverses the network or the complexity of the attacks launched against the network. Therefore, the design of Internet Early Warning Systems (IEWS) enables the early detection of threats in the network, possibly avoiding eventual damages to the network resources. The IEWS works as a sink that collects alerts from different sources (for example, from different IDS), centralizing and correlating information in order to provide a holistic view of the network. This way, the current dissertation describes an IEWS architecture for correlating alerts from (geographically) spread out IDS using the Case-Based Reasoning (CBR) technique together with IP Georeferencing. The results obtained during experiments, which were executed over the implementation of the developed technique, showed the viability of the technique in reducing false-positives. This demonstrates the applicability of the proposal as the basis for developing advanced techniques inside the extended IEWS architecture.
Sistemas de Detecção de Instrução (Intrusion Detection Systems IDS) são projetados para monitorar possíveis ataques à infraestruturas da rede através da geração de alertas. Com a crescente quantidade de componentes conectados na rede, os IDS tradicionais não estão sendo suficientes para a efetiva detecção de ataques maliciosos, tanto pelo volume de dados como pela crescente complexidade de novos ataques. Nesse sentido, a construção de uma arquitetura Internet Early Warning Systems (IEWS) possibilita detectar precocemente as ameaças, antes de causar algum perigo para os recursos da rede. O IEWS funciona como um coletor de diferentes geradores de alertas, possivelmente IDS, centralizando e correlacionado informações afim de gerar uma visão holística da rede. Sendo assim, o trabalho tem como objetivo descrever uma arquitetura IEWS para a correlação de alertas gerados por IDS dispersos geograficamente utilizando a técnica Case-Based Reasoning (CBR) em conjunto com Georreferenciamento de endereços IP. Os resultados obtidos nos experimentos, realizados sobre a implementação da técnica desenvolvida, mostraram a viabilidade da técnica na redução de alertas classificados como falsos-positivos. Isso demonstra a aplicabilidade da proposta como base para o desenvolvimento de técnicas mais apuradas de detecção dentro da arquitetura de IEWS estendida.
Persson, Elias, and Martin Hautamäki. ""Buddy Tracker", an early warning system for recreational divers." Thesis, Karlstads universitet, Fakulteten för teknik- och naturvetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-6386.
Повний текст джерелаPukhanov, Alexander. "WiFi Extension for Drought Early-Warning Detection System Components." Thesis, Linköpings universitet, Elektroniska Kretsar och System, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-123436.
Повний текст джерелаBoulton, Christopher Andrew. "Early warning signals of environmental tipping points." Thesis, University of Exeter, 2015. http://hdl.handle.net/10871/18568.
Повний текст джерелаGadelha, Juliana Rodrigues. "Sea anemones stress responses in three different climatic scenarios as early warning systems for environmental change." Doctoral thesis, Universidade de Aveiro, 2015. http://hdl.handle.net/10773/19133.
Повний текст джерелаCoffman, James Wyatt. "Web-enabling an early warning and tracking system for network vulnerabilities." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA397344.
Повний текст джерелаPapadimitriou, Achillefs. "Optimization of the seismic early warning system for the Tohoku Shinkansen." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/35048.
Повний текст джерелаIncludes bibliographical references (leaves 148-150).
by Achillefs Papadimitriou.
M.S.
Bardwell, Kristina, and Kristina Bardwell. "Evaluation of the Early Warning System at Banner Desert Medical Center." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/621108.
Повний текст джерелаShealy, Linda. "Building an Early Warning System to Identify Potential High School Dropouts." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145278.
Повний текст джерелаWinkler, Susann, Julia Werneke, and Mark Vollrath. "Timing of early warning stages in a multi stage collision warning system: Drivers' evaluation depending on situational influences." Elsevier, 2016. https://publish.fid-move.qucosa.de/id/qucosa%3A33941.
Повний текст джерелаPhinney, Robi. "Developing and Testing an Early Warning System to Improve High School Graduation." Thesis, University of Oregon, 2016. http://hdl.handle.net/1794/20440.
Повний текст джерелаRyan, Zola. "Establishment and evaluation of a livestock early warning system for Laikipia, Kenya." Texas A&M University, 2003. http://hdl.handle.net/1969.1/2261.
Повний текст джерелаRoesler, Scott G. "A Production Early Warning System (PEWS) model which predicts future USAREC mission accomplishment." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA289750.
Повний текст джерелаJoule, Dennis E. "The Intersection of Early Warning System Data and the Lived Experience of Students." Thesis, Lewis and Clark College, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10605934.
Повний текст джерелаMany large urban school districts have implemented Early Warning Systems (EWS) in order to track and organize student data related to their progress toward graduation. The popularity of EWS has increased over the past decade as a number of research studies have demonstrated claims that the EWS data can be used to predict, to a certain degree of accuracy, which students will graduate on time (Bowers, 2010; Bruce, Bridgeland, Fox, & Balfanz, 2011). However, dropping out is not always a decision, but rather the outcome of a long journey of school experiences and life factors that set students on a path to become a dropout or graduate (Rumberger, 2011a). In this case study, interviews conducted with four twelfth-grade students reveal complex lived experiences related to their data in the EWS. This study used Dewey’s (1938) theory of experience as a theoretical framework to better understand how the students’ lived experiences help explain the data recorded in the EWS. Results of this study indicate that, while students describe similar objective conditions of school, they each walk into the school building with unique internal conditions. It is ultimately the interaction between each student’s internal conditions and the objective conditions in school that create the experience they have there. Without a better understanding of the interaction between a student’s internal conditions and the objective conditions that are influencing each student’s experience, districts and schools will be left with an intervention “guessing game.” It is the charge of educators in schools and at the district level to create processes that use the data in the EWS to develop improved practices in the school, and most important, the classroom. The data in the EWS are virtually useless if they do not lead to improved school routines and teacher effectiveness.
Alhasanat, H. A. "Early warning system guidance to mitigate flash flood impacts in Petra region, Jordan." Thesis, University of Salford, 2017. http://usir.salford.ac.uk/44382/.
Повний текст джерелаAktan, Sinan [Verfasser], and Svetlozar T. [Akademischer Betreuer] Račev. "Early Warning System for Bankruptcy: Bankruptcy Prediction / Sinan Aktan. Betreuer: S. T. Rachev." Karlsruhe : KIT-Bibliothek, 2012. http://d-nb.info/1019790032/34.
Повний текст джерелаIgwe, Dorothy C., and Dorothy C. Igwe. "Practitioners' Perception of Implementing the Pediatric Early Warning System (PEWS) in Primary Care." Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/624474.
Повний текст джерелаGonçalves, Gil Pereira. "Sistema Biológico de Alerta Precoce de Contaminantes nos Estuários: desenvolvimento e aplicação no bivalve marinho Mytilus edulis." Master's thesis, 2016. http://hdl.handle.net/10362/50896.
Повний текст джерелаSega, Tsholofelo Dineo. "Conflict early warning systems: its challenges and the continental early warning system." Thesis, 2017. https://hdl.handle.net/10539/24213.
Повний текст джерелаThe international community's dynamics have undergone significant changes since 1990s. Famine, economic, security, and ethnic and religious animosities have greatly contributed to the emergence of conflicts globally. Preventive approaches, tools and structures in dealing with emerging conflicts rapidly became global trend. Early warning systems (EWS) were such preventive tools that bodies such as the African Union (AU) and the three regional economic communities (RECs) in Southern and West Africa and the Horn of Africa adopted to prevent conflicts on the African continent. [Abbreviated Abstract. Open document to view full version]
XL2018
Chen, Shao-Wei, and 陳紹維. "Risk-based Drought Early Warning System." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/83397054642501446990.
Повний текст джерела國立臺灣海洋大學
河海工程學系
97
In this research, an early warning system was developed and proposed for drought management on the real-time reservoir operation. The system consists of three essential elements, namely, (a) drought watch, (b) water consumption measure, and (c) policy making. A Drought Alert Index (DAI) was used to characterize the alert level of drought severity. In addition, this study presents a risk-based decision model integrated into a drought early warning system (DEWS) for reservoir operation. Aspects of posterior risk, the corresponding options to given chances was provided to help decision makers to make better decisions. Decision makers can understand the inclination of attitude associated with any specific probability, and learn to adjust their attitudes in decision-making process. Besides, a user-friendly decision support system (DSS) for drought early warning system on DEWS has been introduced with an eye to practical use. As a pioneering experiment, the Tsengwen and Wushantou reservoirs in southern Taiwan were tested. The results show that the developed risk-based drought early warning system can really react to droughts occurred. The system can assist reservoir managers to work out applicable rule for real-time reservoir operation.
"Contribution of the Governing Council/Global Ministerial Environment Forum of the United Nations Environment Programme to the World Summit on Sustainable Development : note /." [New York] : UN, 2002. http://daccess-ods.un.org/access.nsf/Get?Open&DS=A/CONF.199/PC/9&Lang=A.
Повний текст джерелаUN Job no.: N0230044 E. Material type: Resolutions/decisions (UN). Issued under agenda item 1, agenda document A/CONF.199/PC/1.
楊奕新. "The Comparison of Financial Early Warning System." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/14725830316477512728.
Повний текст джерела國立政治大學
行政管理碩士學程
98
Financial early warning system is a line both in the nature of financial management and operational evaluation of the dual function. To the financial crisis, With the role of prevention and warning system. The significance of means in accordance with relevant laws and regulations of the financial business and financial management principles. Certain number of selected variable set of a number of warning function, indication), cutoff or decimal value, discriminant model. According to the number of data, after testing with the accounting, it cause alarm or signal, so that the issue of the fail to meet the requirement, beyond the scope of the warning or to derail the number of abnormal conditions. To encourage the competent authorities or financial institutions (or banks) early attention to itself. By prevent and promptly correct and improve, to promote the sound management of the system. In recent years, financial institutions have become increasingly complex business and responsible for financial supervision authorities increasingly heavy responsibility, under the influence of the financial internationalization and liberalization. To solve this dilemma, how to make the best use of off-site monitoring tool, make up for lack of spot checks. It should be an effective program to strengthen the current financial supervision system. We all know that more and more attention to the financial supervisory authorities to the work of off-site monitoring. One of the most well-known and effective functioning is the “financial early warning system”. It could assess the performance of financial institutions, financial institutions and the issue of screening show that the functions of the police. For the financial supervision authorities, one of the important auxiliary tool, today. Keywords: financial early warning system, financial institutions, financial supervision
Lin, Yi-Pei, and 林奕霈. "The application of drought early warning system." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/77919396919806367841.
Повний текст джерела國立中興大學
土木工程學系所
101
Water is vital resource essential to life. Apart from droughts and floods struck in recent years, Taiwan has been affected by the other elements leading to unstable water supply such as industrial transformation and changes of water consumption structure. Unstable water supply would cause not only public panic but also social and economic losses. This study aims at developing scenario-based emergency planning for large-scale drought. Because drought is a chronic problem with slower progress than the other natural disasters, strict reservoir monitoring would be helpful in strengthening drought warning system. In this study, we use reservoir inflow and storage conditions as the basic parameters to strengthen warning mechanism, such as the current and history record of reservoir inflow, storage capacity, and water consumption plan. By calculation of the water balance, we estimate the storage capacity of reservoir within a certain period of time in the future. Furthermore, we also predict the possible changes resulting from different drought conditions as well as water supply and distribution strategies The research targets in this project are Feitsui Reservoir and Shimen Reservoir. The data from drought years are used to compare the operation of drought warning models in this study, and rule curve operation. Through this model we can find that, selected long times (90days) operation was too sensitive, caused nuisance. So we suggest that choosing the short times (60days) operation in this drought early warning system.
Liang, Uen-Chin, and 梁雲清. "Optical Early Warning System for Oil Spill Monitoring." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/50591013451104843391.
Повний текст джерелаLIU, SEN-LIN, and 劉森林. "REGRESSION ANALYSIS APPLIED ON SEWAGE EARLY WARNING SYSTEM." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/27769173935111476973.
Повний текст джерела大同大學
工程管理碩士在職專班
104
DanShui River sewage systems (herein after referred to as the present system) large domestic market Basin counties of sewage systems, the plant stations are located in Taipei, New Taipei and Keelung, Taipei, including Taipei City and suburban sewage systems two parts, which covers the new Taipei City Luzhou、Sanchong、WuGu、XinZhuang、BanChiao、ShuLin、ZhongHe、YongHe、TuCheng、XinDian、ShenKeng、SanXia、TaiShan、XiZhi and BaLi other 15 districts and Keelung the QiDu、NuanNuan and AnLe other areas ,Taipei and suburbs excess sewage was collected together via facilities to transports.。 Such a huge and complex pipeline system, according to current experience shows that when rainfall events occur, even turned off all the sewage pumping station related upstream closure station, various sewage pumping station pumps are still much larger than the load condition when the sunny happen, it is necessary closure on stations and stations estimate the amount of water entering the dependency resolution and velocity of the system, the pumping station for the downstream flow of the estimated time as emergency decision making, to avoid the unexpected influx of large amounts of sewage, causing pumping stations flooded station and equipment damage and other disaster damage. In this paper, the current status of research, based on plant-based monitoring stations monitoring equipment in normal operation, the water level and flow rate data capture, calculate the measured flow value via Manning formula, but because of where the flow meter is located below the surface of sewage wastewater vulnerable covered or foreign body impact damage, resulting in distortion was measured flow data or zero, and can not use, so this research method is based on the current equipment is not damaged collected reliable water level and velocity values in order to obtain the flow rate value, and then based on the water level and flow to find the relationship is more than 0.6 above data regression analysis to find the right formula of linear regression, future until after the flow meter used for some time, often due to failure or distortion, the level of information which can be substituted into the regression equation to strike an appropriate the flow rate value to the correction period is missing or distorted information. At present, the research results have been applied to the monitoring station when the normal period of time, measured value and the regression equation calculation value is not much difference, but when the system is abnormal, the measured value is zero or negative, the regression equation calculation value remains stable the precise effect, then the system regression formula is not static, still need regular monitoring every year to the years when the instrument repair and maintenance, accounting together again this regression formula, just as the period of time after the test instrument calibration should be performed is the same reason。
Yamg, Chih-Hsiang, and 楊智翔. "Drought Early Warning System on Ming-Te Reservoir." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/16953756070011166284.
Повний текст джерела國立臺灣海洋大學
河海工程學系
95
In this research, a color-coded early warning system is developed and proposed for drought management on the real-time reservoir operation. The system consists of three essential elements, namely, (a) drought watch, (b) water consumption measure, and (c) drought alert analysis. A new Drought Alert Index is used to characterize the alert level of drought severity. For demonstration, the drought warning procedures were effectively applied to the Ming-Te reservoir. The results show that the developed drought watch can really react to droughts occurred. The implementation of such a system proves that the decision support-like system can help the water authorities concerned take a timely action while confronting drought threats. Keywords: Drought alert index,Drought watch, Early warning system.
Chen, Hung-Chih, and 陳泓志. "Financial Early Warning System: An Integrating Logit Model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/09378326193038453954.
Повний текст джерела臺灣大學
財務金融學研究所
98
This paper aims to build a more predictable financial early warning system for Taiwan companies with Binary Logit model. We integrate traditional Expert system and Logit model, using five categories of variables including accounting variables, market variables, corporate governance variables, accountant variables, and macroeconomics variables, to build an integrating Logit model which conforms to expert system’s spirit that uses lots of information and does not lack in objectivity and theoretical background. We examine the one year later predict accuracy of corporate financial distress, and the changes in predict ability when continually adding each variable. We also examine the prior studies variables’ significance of affecting the predict ability. We find that after considering the five categories of variables, the expert system integrating model’s in-sample predict accuracy is 90.9%, slightly higher than accounting model’s 90.0%; and out-sample predict accuracy is 95.6%, also higher than accounting model’s 93.4%, especially the predict accuracy in financial distress companies growing from 65.9% to 84.4%. We conclude that all the five categories of variables have significant effect to financial distress prediction, and accounting variables have the best explanatory power, market variables are the second best one, but the other variables’ explanatory power are much weaker. In predict ability, we can get 90% predict accuracy when only using accounting variables, showing that accounting variables are still the most important factor. We also can improve the predict accuracy and explanatory power when adding other variables, and the market variables and macroeconomic variables especially have the higher contribution.
Hsieh, Hsueh-wei, and 謝學維. "A Watershed-based Debris Flow Early-warning System." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/45898396183682231616.
Повний текст джерела逢甲大學
資訊電機工程碩士在職專班
99
In Taiwan, debris flow disaster have been increasing in recent years due to various factors, such as complex earthquake faults, geographic layers of shattered rocks, high and steep mountains, concentrated rainfall, plus the overdevelopment of hillsides that result in soil erosion and water loss. Debris flows often bring a lot of rocks and mud causing a threat to the property and even the safety of the residents in the affected areas. With more and more extreme rainfall events as a result of climate change, the debris flow warning system is an effective notification mechanism for early-warning the disaster. However, the current system collects precipitation through Central Weather Bureau, which number of precipitation stations is not enough and rainfall situation is greatly affected by terrain cause the problems of imbalanced rainfall distribution. Therefore, the system can’t collect accurate rainfall data and cause accuracy of the system is not enough. This thesis proposes a watershed-based debris flow early-warning system which applies OGC SWE standard. The system uses the standardized data exchange mechanism to integrate and share heterogeneous monitor resources. In this way, the system can high density monitor the debris-flow-prone area. In addition, this thesis introduces a watershed-based sensing model and a rainfall warning decision method for the requirement of automatic debris flow early warning. Those mechanisms enable the system to collect sensing data under dependencies relationship and issue warning messages automatically. Moreover, SWE software provided by 52North is used to implement the proposed watershed-based debris flow early-warning system prototype. Finally, we use the historical rainfall data to compare and analyze the proposed rainfall warning decision method. According to experimental results, the proposed system can collect sensing data more accurate and advance the time of issue warning messages efficiently.
Liao, Chih-Wei, and 廖治瑋. "An Early Warning System in the Stock Market." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/19925359706172289400.
Повний текст джерела銘傳大學
經濟學系碩士班
99
During the period of a long market, there always can have easy targets for investment in the stock market. Once the optimistic mood emerges, irrational investors will certainly push the stock market to an even higher level. However, if co-movements of different industries occur and pass a threshold level, then the whole stock market can fall unexpectedly more than 200 points in the Taipei stock market in one day. By analyzing the WINDEX of the market and every individual industrial index,this study tries to reveal an early warning signal one day before a more than 200 point decline will happen. Basically, the phase transition of up-turn into down-turn co-movements of a majority of industrial indexes will be examined to serve as the early warning signal.
Lin, Chi-Ying, and 林其穎. "Experimental Study On Bridge Scour Early Warning System." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/08372464390861353591.
Повний текст джерела國立臺灣大學
土木工程學研究所
99
Taiwan is the island which is well known for its distinctive topography features. The central mountain range bisects the land from north to south resulting in most rivers have short courses and rapid streams. As a result, the scour effect could be seem as a critical problem for the bridge structure as the scale of natural disasters increase. The growing amount of bridge failure events in Taiwan due to typhoons and floods in recent years causing the public pay more and more attention towards the bridge safety under natural disaster, and the government and related organization also put a lot of efforts on such problem. This dissertation applies five kinds of sensing units which is based on the same sensing mechanism of developed scour monitoring system to laboratory experiments. Sensing units includes micro-electro-mechanical systems based pressure sensors, vibration-based detection sensors, floating ball, inner camera and handheld camera. The main purpose of this research is to verify the feasibility of developed monitoring system and to establish a warning benchmark by conducting the various test using reduced scale bridge structure model in laboratory. The feasibility of the developed monitoring system has been verified in laboratory by several experiments. The scour depth measurement by using accelerometers and the floating ball have been successfully applied to experiments, and it could be observed and confirmed that the scour depth can be regarded as the major parameter for the safety evaluation of caisson foundation bridge. Modes of scour failure for bridge structure are complex with many uncertainties, but the proposed sensing mechanisms for scour early warning could be achieved.
Chen, Kang-Rung, and 陳康容. "Financial Early Warning System Models of Taiwanese Banks." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/4qk365.
Повний текст джерела國立虎尾科技大學
經營管理研究所
98
Since 1980, Taiwan’s government relaxes restrictions of banks gradually, new banks establish induce the competition intense in bank-industry. And government strengthened banking supervision and practiced financial reform bills actively. Therefore, banks to face the sudden changes in the financial environment that management of risk is an important issue. This article using financial information among 33 domestic banks from first season in 2004 to the fourth season in 2008, using CAMELS ratings to assess the bank operating performance. The early warning model using Logit regression analysis to set up the non-risk model and risk model. That can be reference for financial inspection units and related financial institutions. The Empirical research results indicate as follows: (1) Select by factor analysis variables that consistent with CAMELS (Capital Adequacy、Asset Quality、Management、Earning、Liquidity、Sensitivity to market risk) that means this article can objectively evaluate the bank performance. Hence, that can reference for the relevant institutions and investors. (2) Use Logit regression analysis set up original sample models that prediction ability are:non-risk model A is 72.73% and risk model B is 78.79%. Predictive sample models of prediction ability:non-risk model A is 90.91% and risk model B is 96.97%. (3) The CAMELS of non-risk models has good predictive ability, the model add risk indicators that predictive ability and type I error work better than non-risk models.
Liu, Chuan-Chih, and 劉傳智. "An Application of Early Warning System of Consumer Loan." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/21179841061506696410.
Повний текст джерела淡江大學
國際貿易學系碩士在職專班
91
This study focuses on the building of risk warning system for the purposes of facilitating consumer banks’ credit management procedure. Using data consumers’ socioeconomic as well as their previous records concerning credit worthiness, two multivariate analysis method, the canonical discriminant analysis and the logistic discriminant analysis, are applied to construct a formula that can distinguish a good borrowers from the bad one, and that can be used for evaluating potential loan customers to effectively shorten the evaluation procedures. Samples of size 3,036 customers were drawn from the database of a specific bank in Taiwan. The sample was divided into two groups: one that consists of 2,581 (85%) observations, were used for model estimation; and the remaining 455 (15%) were acting as the test sample for model evaluation purpose. The results from the test sample simulations have shown that estimation based on the logistic discriminant analysis performs a little bit better than those conducted by the canonical discriminant analysis. However, the former was not able to discriminate the middle and the higher risk groups.
Chou, Hsing-Kuo, and 周興國. "Application of Earthquake Early Warning within Intelligent Building System." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/43cn8d.
Повний текст джерела國立臺北科技大學
土木與防災研究所
99
Intelligent building system has the central management and control device functions, including remote monitoring, operation, control, recording and management. By building an integrated safety system platform, access control, surveillance, air conditioning, lighting, fire, electrical and other equipment used to control the management, operation and maintenance of monitoring equipment operation and maintenance records, in order to achieve safety, improve efficiency and save staff costs and energy conservation management purposes. In this study, design and development of intelligent building systems research, the first intelligent building systems in the current structure and function, a second analysis of the applicability of seismic instant alerts, and to explore the global business intelligent building system, building systems and functions framework, the survey found that the development of various business systems to an open integration platform, and IP-based architecture, Web browsers and wireless networking module. Then, by the survey result of the business intelligent building and the functional requirements, developing and designing the new intelligent building systems and a new functional module of earthquake early warning, choosing an existing building into the intelligent building systems and the function of earthquake early warning to create a complete intelligent building systems and earthquake early warning function. Intelligent building systems and building almost merged into one, commonly used in construction management, earthquake early warning proposed in the current building with intelligent building systems commonly used in the field of earthquake disaster prevention in order to reduce the losses caused by disasters.
Hsu, Sheng-Chieh, and 許勝傑. "Risk-based Drought Early Warning System in Keelung Area." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/47078832700828764020.
Повний текст джерела國立臺灣海洋大學
河海工程學系
97
In this research, an early warning system was developed and proposed for drought management on the real-time reservoir operation. The system consists of three essential elements, namely, (a) drought watch, (b) water consumption measure, and (c) policy making. A Drought Alert Index (DAI) was used to characterize the alert level of drought severity. In addition, this study presents a risk-based decision model integrated into a drought early warning system (DEWS) for reservoir operation. Aspects of posterior risk, the corresponding options to given chances was provided to help decision makers to make better decisions. Decision makers can understand the inclination of attitude associated with any specific probability, and learn to adjust their attitudes in decision-making process. Besides, a user-friendly decision support system (DSS) for drought early warning system on DEWS has been introduced with an eye to practical use. As a pioneering experiment, Keelung Area was tested. The results show that the developed risk-based drought early warning system can really react to droughts occurred. The system can assist reservoir managers to work out applicable rule for real-time reservoir operation.
Wu, Chun-Hui, and 吳俊輝. "Early Warning System for Emerging Europe and Latin America." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/78569148760978798907.
Повний текст джерела國立臺灣大學
國際企業學研究所
97
The main purpose of this thesis is to provide a measure of the probability of crises related to a aggregate index. Firstly we set a market index pressure to measure when a nation experienced currency crisis. Secondly, given a group of economic variables, we use Signal Approach suggested by Berg and Patillo (1999)、Goldstein (2000)、Kamisky and Reinhert (1998)、Edison to find which variables can have signals before the real crises happen. Finally, these workable variables would be used to set up an early warning system to predict the possibility of crises. Our warning system includes twelve nations: Argentina, Chile, Czech, Estonia, Hungary, Israel, Latvia, Lithuania, Poland, Romania, Slovakia, Turkey and also ten economic variables.
Chang, Chieh-Hsiang, and 張傑翔. "Apply Data Mining Approaches in Financial Early Warning System." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/99158219835011321311.
Повний текст джерела華梵大學
資訊管理學系碩士班
95
Financial Early warning system can not only help the management of the financial institutions but also diagnose their common operations. Since the early 1970s, many related researches have already made. However, most of them use traditional statistic ways to build the early warning system until recent years. Because of the vigorous development of the data mining techniques, many researches begin to apply those techniques to various fields also including early warning system. Data mining doesn’t need to satisfy many statistical antecedent assumptions and can transform enormous original data into meaningful and useful information. To build the early warning system model, the related financial laws, data, and operation management rules need to be taken into consideration. However, the number of features is too large and not all of them are helpful to prediction. Data sets with unimportant, noisy or high correlated features will significant decrease the classification accuracy rate. By removing these features, the efficiency and accuracy rate can obtain a better result. Back-propagation neural network (BPN), support vector machine (SVM) and decision tree (DT) are well-known data mining techniques, which can be applied to various fields and have higher classification ability. However, data mining techniques may suffer the problem of parameters settings. Bad parameter setting of data mining techniques will result worse accuracy rate. Therefore, this paper utilize one meta-heuristic, particle swarm optimization (PSO), to obtain suitable parameter optimization and select a subset of feature without degrade the classification accuracy rate. By the meta-heuristic global search characteristic, the parameters of BPN, SVM and DT can be optimized and the feature selection can be done at the same time to obtain the minimum set of features which can result in higher accuracy effectively. In order to evaluate the proposed approach, this research taken the report of the Taiwan Ratings to be the authority. The “Condition and Performance of Domestic Banks” from the Central bank of China, Republic of China (Taiwan) and the “Statistics of Financial Institutions” from the Financial Supervisory commission, Executive Yuan are planed to be the source data. Banks will be classified as one of three categories ( ”well”, ”average”, and ”risky”). In the experiment, although BPN and SVM have the high accuracy of forecast, the processes among them are black-box testing. Professionals can’t take these results into their future judgments. By the tree structure which was obtained from the proposed PSO+DT architecture, experts can obtain the best decision rules and thus make further evaluation and correction of our early warning system model. The experiment results shown that our proposed approaches can reduce unnecessarily features and improve classification accuracy significantly.
王姵茹. "The Application of XBRL to Early Banking Warning System." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/55987419426386533768.
Повний текст джерела國立中正大學
會計學研究所
92
The traditional method of field supervision has become inadequate due to the continuing emergence of new banks, the openness of various banking business and the short of human resource for financial supervision. To effectively utilize the resource of financial supervision, there is a need for revolution on financial supervision method. A early banking warning system facilitates financial supervision working mainly in that it screens banks and list those to note with priority, so as to utilize the financial supervision effectively and find out problematic banks in time. This research, in the base of the CAMELS Rating System proposed by the FFIEC, studies the government-required report data from banks and the related codes to suggest the index of evaluation for early banking warning system. The researcher used the Web Service to obtain data needed, which can obtain data from the target banks anywhere and anytime. The researcher then, according the second version of the XBRL standard and with the technique of XPath, established a standard taxonomy package of early banking warning system, edited the reports of XBRL early banking warning system automatically with the practice of early banking warning analysis prototype, and collected all the reports from the target banks. The method of percentile ranking was used to elicit the risky or unqualified banks to cross-validate the taxonomy standard established
Chou, Chi-Chen, and 周繼成. "The Early Warning System of Banking Industry in Taiwan." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/64628821646074190627.
Повний текст джерела國立臺灣大學
財務金融學系
86
In the trend of liberalization in banking industry, sixteen newly-established banks were permitted to operate after 1991 and the operation risk were increasing. The purpose of this thesis is to focus on the newly-established and long existing banks to analyze their financial soundness and safety. Logit and Probit are used to build up an early warning system for Taiwan Financial Institutions and I also compare these two models. The sample data starts from 1992 to 1997. Some conclusions are drawn from my empirical study: (1) The newly-established banks, which are grouped into the worse-side, perform worse than old banks. (2) Probit model works better than Logit model in terms of the correct judgment, Type I Error, and Type II Error. (3) The number of banks on the worse-side increases from 1992 to 1997, which reflects the increasing risk on bank industry. (4) After Factor analysis, the remaining financial variables, which are still consistent with CAMEL model, accumulate enough power to fit the early warning system.
Lin, Yu-Cun, and 林育村. "Development of very early warning system graphic control program." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/50021156160237177435.
Повний текст джерела國立雲林科技大學
機械工程系
103
Firstly, this study fluid mechanics equations to establish mathematical model of pressure loss and capillary air sampling network and derive the mathematical model of the flow orifice, In order to make the results very early warning systems scada systems and reduce the actual experimental error, so we have to do the actual experiment, the results we got with Excel to establish a series of related samples and best wind speed of the capillary tube, then these best Winds database connected to the pattern control program allows pattern control program to achieve a more accurate calculation of output accuracy and more appropriate status, again derived using a mathematical model and then create a Execl as a pre-production step of writing diagram programming, Execl made available to verify that the design process, the program is correct at the time of writing code. Finally, these mathematical models can be pre-set with InduSoft write to know the actual detection of air information scada program that has allowed the engineer or operator knows the actual installation information to know, but cut the correct installation, improve warning effect. Keywords: very early warning systems、hydrodynamics、InduSoft、air scada program information
Kung-Hung, Cheng, and 鄭功宏. "A Study of Intelligence Floods Early Warning Information System." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/72911820471105978055.
Повний текст джерела華夏技術學院
資產與物業管理研究所
100
Owing to the global climate changes in recent years, torrential rains always flood to cause serious disasters. For instance, 3,004.5 mm, 1,861 mm and 1,105,5mm rainfalls at Alishan, Chiayi (called as 88 Flood), Datong, Yilan and Manchou, Pingtong were caused by Typhoon Morakot, Magi and Nanmadol in 2009, 2010 and 2011; 610 Flood in 2012, followed by Typhoon Talim and Tembin, caused huge images. If such rainfall takes place in Taipei area, it will cause flood. Furthermore, there are a lot of high buildings in Taipei. The flood will cause the vehicles and electrical equipment on the basement as well as the public’s properties to seriously damage. Therefore, we study the installation of the Intelligence Early Warning System shortly before flooding, which automatically sends a warning message via mobile phone to tell owners and securities while the accumulated rainfalls and the ponding level reach the warning value, so that can immediately evacuate to reduce flood losses. The purpose of this study is to utilize the digital rain gauge and digital level gauge during the typhoon or torrential rain to monitor the rainfalls and the ponding depth of ground surface. With the warning rainfall from Disaster Prevention Information Website of Water Resources Agency, the Ministry of Economic Affairs and using the hydraulic analyses to investigate the characteristics of the regional drainage system, the warning rainfall and ponding level can be calculated. The Intelligence Early Warning System will automatically message owners and securities by PLC to acquire the data from the digital rainfall gauge and digital level gauge when reaching the warning value to evacuate immediately, so that can reduce property loss and avoid casualties. This study is to install the Intelligence Early Warning System at Chonghe as an example, follow the warning rainfall at the first and second grade from Disaster Prevention Information Website of Water Resources Agency, the Ministry of Economic Affairs, make use of reasonable formula to evaluate the flood flow for resident district and assume the community use two-year rainfall strength formula to design the drainage during the reconstruction from Construction and Planning Agency, Ministry of the Interior, to calculate the ponding depth caused by the warning flow corresponding to the warning rainfall at the first and second grade as the warning threshold under “normal drainage” and “completely no drainage”. This study tests the system when modeling the sand box and evaluates at Chonghe. Since rainfall is extended within one hour, the system will issue the second-grade warning when the ponding depth reaches 31.63 cm; when the ponding depth reaches 47.44 cm, the system will issue the first-grade warning. Since rainfall is extended within three hours, the system will issue the second-grade warning when the ponding depth reaches 63.25 cm; when the ponding depth reaches 86.97 cm, the system will issue the first-grade warning. Since rainfall is extended within six hours, the system will issue the second-grade warning when the ponding depth reaches 94.88 cm; when the ponding depth reaches 118.59 cm, the system will issue the first-grade warning. Since rainfall is extended within 12 hours, the system will issue the second-grade warning when the ponding depth reaches 126.50 cm; when the ponding depth reaches 158.13 cm, the system will issue the first-grade warning. Since rainfall is extended within 24 hours, the system will issue the second-grade warning when the ponding depth reaches 158.13 cm; when the ponding depth reaches 197.66 cm, the system will issue the first-grade warning. The Intelligence Early Warning System in this study not only monitors the rainfalls and the ponding depth immediately, but also automatically messages and proposes the early warning to evacuate so that can avoid property losses and make concrete contribution.
Tung, Lun-Chien, and 董倫傑. "Research and Development of Rolling Blackout Early Warning System." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/whnujm.
Повний текст джерела國立臺灣科技大學
電機工程系
106
The purpose of this thesis is to study and develop an early warning system of rolling blackout for Central or local Emergency Response Center and disturbed users. Taiwan government actively promotes “2025 non-nuclear homeland”, “green energy” and “sustainable energy” policies, coupled with the difficulty of new power plant erection and the resistance of environmental protection group, the system operating reserve deficient is not rare, and the risk of power shortage is greatly increased. On August 15, 2017, all 6 units of the Da-Tan Power Plant were tripped simultaneously due to the sudden interruption of natural gas supply. The unexpected event results in severe power blackout around entire Taiwan and affects the power supply of 5.92 million users. Nowadays, Taiwan Power Company still deficiencies in early warning mechanism for rolling blackout. It causes inconvenience, anxiety and economic loss to the local enterprise and the public and influences the people's livelihood as well. If there is an early warning mechanism, economic loss may be significantly reduced and the public's nervousness and hesitations will also be alleviated. In this thesis research, Visual C# is applied to develop an early warning system for Taiwan Power Company to provide advantageous information to Central or local government response center and affected users for emergency reaction . The proposed early warning system combined with geographic data can, therefore, provide following valuable information: (i) power blackout facts of traffic sign system, (ii) power blackout data for hospitals, schools, and public, and (iii) advanced power blackout notices to the households by mobile phone messages.
HSIA, PEI-SHAN, and 夏霈珊. "Warning System Indices for Banks in Taiwan and Relationship between Early Warning and Risk Management." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/98923489609518992281.
Повний текст джерела世新大學
財務金融學研究所(含碩專班)
103
This analysis is based on 26 banks Capital Adequacy Ratio and Warning System Indices.The data from January, 2003 to December, 2014. Set up January, 2008 data as the cutoff point separate it into two periods, before and after financial crisis. We utilized Granger Causality Test, Vector Auto-regression Model, and Impulse Response Analysis to find the connection between banks Early-Warning System and risk management. The result of the research indicates that before financial crisis, Capital Adequacy Ratio has positive impact on Overdue Interest ratio, but negative impact on Operating Expense Ratio; after financial crisis, Capital Adequacy Ratio and Early-Warning Indices have close relationship between them. Capital Adequacy Ratio has positive impact on Debt Ratio, has first reduced, then increased impact on Return On Asset and Earning Before Tax Margin, and has negative effect on Overdue Interest Ratio and Operating Expense Ratio. It is concluded that the Early-Warning Indices and Capital Adequacy Ratio affect each other, and more close related after financial crisis. The efficiency of loan quality, and asset utilization will impact Capital Adequacy Ratio. Capital Adequacy Ratio has negative impact on Operating Expense Ratio and Overdue Interest Ratio, so higher the Capital Adequacy Ratio, the lower Operating Cost it will be. The loan quality will improve, and it will control risk more effectively.
Kuo, Zi-Ping, and 郭子平. "A Early Earthquake Warning System and Dental Occlusion Pressure Distribution Monitoring System." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/7tmrb9.
Повний текст джерела國立臺北科技大學
電腦與通訊研究所
101
There are two implementation in this thesis. Earthquake early warning system and dental occlusion pressure distribution. Taiwan is located in the circum-Pacific seismic belt; the earthquakes often caused great damages on life and infrastructures. In the metropolis, the population increasingly intense, destructive earthquake caused heavy casualties. For example, on September 21, 1999, the 921 earthquake resulted in approximately 2321 people were killed and more than 8,000 injured and property loss of about NT$ 30 billion. If people early be informed that the earthquake is coming, it will reduce the loss of casualties. In this design, the earthquake early warning system is desinged according the research recently. Second part of this paper presents a tooth bite force sensing system, mainly used in dental implants applications, especially for dental occlusion force distributed reference. The proposed system consists of soft resistive pressure sensor, which serves as the sensing element of the occlusion force. Moreover, the soft pressure sensors collect the measured pressure to perform the precise amount of uneven teeth surface. Furthermore, a graphical color changes manner showing the tooth size of the force are developed in this work.
Bosi, Anna [Verfasser]. "Early-warning monitoring system for masonry structures / by Anna Bosi." 2009. http://d-nb.info/993374107/34.
Повний текст джерелаLin, Yu-Ling, and 林于令. "A Study on the Early Warning System of Military Project." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/74042586167175002234.
Повний текст джерела國防大學國防管理學院
國防資訊研究所
97
The idea of military construction as a whole can be broken down into the plans and the projects, which have priority and with closely together characteristics, so the costs and the losses of one project’s failure is usually the tip of the iceberg , and follows by planning delays and the cost due to modification is impossible to assess. So the study try to research and to analyze by the implementation of the army budget case and with the projects review of the data ,through test of independence and t-test to find out a significant impact on the military control of the project with the implementation of significant factors, and construct of an appropriate early warning models to provide to the Decision-making unit, as for a sign of crisis in early implementation of projects. The early-warning model of Logistic Model in the study, concludes that the nine variables have a significant impact on the success or failure of projects :executive unit, classes, properties, dependency on the other plans, Commissioned by the unit, budget use, the ration of the selection and budget amount , and the bid opening count. In the circumstances, the model event probability limits of 0.5, the accuracy rate of the forecast the failure probability of the projects is up to 87.6 percent. So the forecast model in the study can provide the project managers in army to forecast the high-risk projects, take further prevention and response action, and to improve the efficiency of the implementation of the budget.