scholarly journals Using Bayesian networks to model watershed management decisions: an East Canyon Creek case study

2005 ◽  
Vol 7 (4) ◽  
pp. 267-282 ◽  
Author(s):  
Daniel P. Ames ◽  
Bethany T. Neilson ◽  
David K. Stevens ◽  
Upmanu Lall
Keyword(s):  
Bayesian Networks ◽  
Watershed Management ◽  
Graphical Model ◽  
Probability Distributions ◽  
Management Decisions ◽  
Management Scenarios ◽  
Northern Utah ◽  
Key Variables ◽  
Recreational Use

An approach to developing and using Bayesian networks to model watershed management decisions is presented with a case study application to phosphorus management in the East Canyon watershed in Northern Utah, USA. The Bayesian network analysis includes a graphical model of the key variables in the system and conditional and marginal probability distributions derived from a variety of data and information sources. The resulting model is used to 1) estimate the probability of meeting legal water quality requirements for phosphorus in East Canyon Creek under several management scenarios and 2) estimate the probability of increased recreational use of East Canyon Reservoir and subsequent revenue under these scenarios.

scholarly journals COMBINING BAYESIAN NETWORKS AND ROUGH SETS: FURTHER STEP TOWARDS REASONING ABOUT UNCERTAINTY

2014 ◽  
pp. 6-14
Author(s):  
Janusz Zalewski ◽  
Sławomir T. Wierzchoń ◽  
Henry L. Pfister
Keyword(s):  
Bayesian Networks ◽  
Real Time ◽  
Rough Sets ◽  
Probability Distributions ◽  
Bayesian Belief Networks ◽  
Critical Systems ◽  
Safety Critical ◽  
Safety Critical Systems ◽  
Number Of Authors

This paper discusses a combination of Bayesian belief networks and rough sets for reasoning about uncertainty. The motivation for this work is the problem with assessment of properties of software used in real-time safety-critical systems. A number of authors applied Bayesian networks for this purpose, however, their approach suffers from problems related to calculating the conditional probability distributions, when there is scarcity of experimental data. The current authors propose enhancing this method by using rough sets, which do not require knowledge of probability distributions and thus are helpful in making preliminary evaluations, especially in real-time decision making. The combination of Bayesian network and rough sets tools, Netica and Rosetta, respectively, is used to demonstrate the applicability of this method in a case study of the Australian Navy exercise.

Investigation of a New Approach to Predict Water Quality Extremes with a Case Study of Chemical Determinands in Stream Water

1991 ◽  
Vol 24 (6) ◽  
pp. 25-33
Author(s):  
A. J. Jakeman ◽  
P. G. Whitehead ◽  
A. Robson ◽  
J. A. Taylor ◽  
J. Bai
Keyword(s):  
Water Quality ◽  
Stream Water ◽  
Probability Distributions ◽  
Management Strategies ◽  
Hybrid Modelling ◽  
Trend Model ◽  
Environmental Extremes ◽  
Modelling Approach

The paper illustrates analysis of the assumptions of the statistical component of a hybrid modelling approach for predicting environmental extremes. This shows how to assess the applicability of the approach to water quality problems. The analysis involves data on stream acidity from the Birkenes catchment in Norway. The modelling approach is hybrid in that it uses: (1) a deterministic or process-based description to simulate (non-stationary) long term trend values of environmental variables, and (2) probability distributions which are superimposed on the trend values to characterise the frequency of shorter term concentrations. This permits assessment of management strategies and of sensitivity to climate variables by adjusting the values of major forcing variables in the trend model. Knowledge of the variability about the trend is provided by: (a) identification of an appropriate parametric form of the probability density function (pdf) of the environmental attribute (e.g. stream acidity variables) whose extremes are of interest, and (b) estimation of pdf parameters using the output of the trend model.

scholarly journals The application of environmental governance for sustainable watershed-based management

2021 ◽  
Author(s):  
Seiichi Kagaya ◽  
Tetsuya Wada
Keyword(s):  
Environmental Protection ◽  
River Basin ◽  
Watershed Management ◽  
Water Use ◽  
Flood Control ◽  
Environmental Governance ◽  
Planning Process ◽  
Environment Assessment ◽  
Control Water

AbstractIn recent years, it has become popular for some of countries and regions to adapt the system of governance to varied and complex issues concerned with regional development and the environment. Watershed management is possibly the best example of this. It involves flood control, water use management and river environment simultaneously. Therefore, comprehensive watershed-based management should be aimed at balancing those aims. The objectives of this study are to introduce the notion of environmental governance into the planning process, to establish a method for assessing the alternatives and to develop a procedure for determining the most appropriate plan for environmental governance. The planning process here is based on strategic environment assessment (SEA). To verify the hypothetical approach, the middle river basin in the Tokachi River, Japan was selected as a case study. In practice, after workshop discussions, it was found to have the appropriate degree of consensus based on the balance of flood control and environmental protection in the watershed.

scholarly journals UAV Forensics: DJI Mini 2 Case Study

Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 49
Author(s):  
Miloš Stanković ◽  
Mohammad Meraj Mirza ◽  
Umit Karabiyik
Keyword(s):  
Law Enforcement ◽  
Federal Aviation Administration ◽  
Easy Access ◽  
Law Enforcement Agencies ◽  
The Past ◽  
Personally Identifiable Information ◽  
Multiple Devices ◽  
Forensic Tools ◽  
Recreational Use

Rapid technology advancements, especially in the past decade, have allowed off-the-shelf unmanned aerial vehicles (UAVs) that weigh less than 250 g to become available for recreational use by the general population. Many well-known manufacturers (e.g., DJI) are now focusing on this segment of UAVs, and the new DJI Mini 2 drone is one of many that falls under this category, which enables easy access to be purchased and used without any Part 107 certification and Remote ID registration. The versatility of drones and drone models is appealing for customers, but they pose many challenges to forensic tools and digital forensics investigators due to numerous hardware and software variations. In addition, different devices can be associated and used for controlling these drones (e.g., Android and iOS smartphones). Moreover, according to the Federal Aviation Administration (FAA), the adoption of Remote ID is not going to be required for people without the 107 certifications for this segment at least until 2023, which creates finding personally identifiable information a necessity in these types of investigations. In this research, we conducted a comprehensive investigation of DJI Mini 2 and its data stored across multiple devices (e.g., SD cards and mobile devices) that are associated with the drone. The aim of this paper is to (1) create several criminal-like scenarios, (2) acquire and analyze the created scenarios using leading forensics software (e.g., Cellebrite and Magnet Axiom) that are commonly used by law enforcement agencies, (3) and present findings associated with potential criminal activities.

scholarly journals Scalable information-theoretic path planning for a rover-helicopter team in uncertain environments

2021 ◽  
Vol 18 (2) ◽  
pp. 172988142199958
Author(s):  
Larkin Folsom ◽  
Masahiro Ono ◽  
Kyohei Otsu ◽  
Hyoshin Park
Keyword(s):  
Path Planning ◽  
Lower Risk ◽  
Information Gain ◽  
Probability Distributions ◽  
Single Agent ◽  
Uncertain Environments ◽  
Information Theoretic ◽  
Highly Correlated ◽  
Naive Approach

Mission-critical exploration of uncertain environments requires reliable and robust mechanisms for achieving information gain. Typical measures of information gain such as Shannon entropy and KL divergence are unable to distinguish between different bimodal probability distributions or introduce bias toward one mode of a bimodal probability distribution. The use of a standard deviation (SD) metric reduces bias while retaining the ability to distinguish between higher and lower risk distributions. Areas of high SD can be safely explored through observation with an autonomous Mars Helicopter allowing safer and faster path plans for ground-based rovers. First, this study presents a single-agent information-theoretic utility-based path planning method for a highly correlated uncertain environment. Then, an information-theoretic two-stage multiagent rapidly exploring random tree framework is presented, which guides Mars helicopter through regions of high SD to reduce uncertainty for the rover. In a Monte Carlo simulation, we compare our information-theoretic framework with a rover-only approach and a naive approach, in which the helicopter scouts ahead of the rover along its planned path. Finally, the model is demonstrated in a case study on the Jezero region of Mars. Results show that the information-theoretic helicopter improves the travel time for the rover on average when compared with the rover alone or with the helicopter scouting ahead along the rover’s initially planned route.

Building Bayesian networks for legal evidence with narratives: a case study evaluation

2014 ◽  
Vol 22 (4) ◽  
pp. 375-421 ◽  
Author(s):  
Charlotte S. Vlek ◽  
Henry Prakken ◽  
Silja Renooij ◽  
Bart Verheij
Keyword(s):  
Bayesian Networks ◽  
Legal Evidence ◽  
Study Evaluation
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