Maximum Product of Spacing Parameter Estimation of Gompertz Rayleigh Distribution and Application to Rainfall Datasets

Gompertz Rayleigh (GomR) distribution was introduced in an earlier study with few statistical properties derived and parameters estimated using only the most common traditional method, Maximum Likelihood Estimation (MLE). This paper aimed at deriving more statistical properties of the GomR distribution, estimating the three unknown parameters via a competitive method, Maximum Product of Spacing (MPS) and evaluating goodness of fit using rainfall data sets from Nigeria, Malaysia and Argentina. Properties of statistical distributions including distribution of smallest and largest order statistics, cumulative or integrated hazard function, odds function, rth non-central moments, moment generating function, mean, variance and entropy measures for GomR distribution were explicitly derived. The fitted data sets reveal the flexibility of GomR distribution over other distributions been compared with. Simulation study was used to evaluate the consistency, accuracy and unbiasedness of the GomR distribution parameter estimates obtained from the method of MPS. The study found that GomR distribution could not provide a better fit for Argentine rainfall data but it was the best distribution for the rainfall data sets from Nigeria and Malaysia in comparison with the distributions; Generalized Weibull Rayleigh (GWR), Exponentiated Weibull Rayleigh (EWR), Type (II) Topp Leone Generalized Inverse Rayleigh (TIITLGIR), Kumarawamy Exponential Inverse Raylrigh (KEIR), Negative Binomial Marshall-Olkin Rayleigh (NBMOR) and Exponentiated Weibull (EW). Furthermore, the estimates from MPSE were consistent as the sample size increases but not as efficient as those from MLE.

ON THE PROPERTIES AND APPLICATIONS OF A NEW EXTENSION OF EXPONENTIATED RAYLEIGH DISTRIBUTION

Statistical distributions already in existence are not the most appropriate model that adequately describes real-life data such as those obtained from experimental investigations. Therefore, there are needs to come up with their extended forms to give substitutive adaptable models. By adopting the method of Transformed-Transformer family of distributions, an extension of Exponentiated Rayleigh distribution titled Gompertz- Exponentiated Rayleigh (GOM-ER) distribution was proposed and proved to be valid. Some properties of the new distribution including random number generator, quartiles, distribution of smallest and largest order statistics, reliability function, hazard rate function, cumulative or integrated hazard function, odds function, non-central moments, moment generating function, mean, variance and entropy measures were derived. Using the methods of maximum likelihood and maximum product of spacing, the four unknown parameters were estimated. Shapes of the hazard function depicts that GOM-ER is a distribution that is strictly increasing while those of the PDF depicts that GOM-ER can be skewed or symmetrical. Two datasets were fitted to determine the flexibility of GOM-ER. Simulation study evaluates the consistency, accuracy and unbiasedness of the GOM-ER parameter estimates obtained from the two frequentist estimation methods adopted.

Integrated mapping of water-related disasters using the analytical hierarchy process under land use change and climate change issues in Laos

In the past few decades, various natural hazards have occurred in Laos. To lower the consequences and losses caused by hazardous events, it is important to understand the magnitude of each hazard and the potential impact area. The main objective of this study was to propose a new approach to integrating hazard maps to detect hazardous areas on a national scale, for which area-limited data are available. The integrated hazard maps were based on a merging of five hazard maps: floods, land use changes, landslides, climate change impacts on floods, and climate change impacts on landslides. The integrated hazard map consists of six maps under three representative concentration pathway (RCP) scenarios and two time periods (near future and far future). The analytical hierarchy process (AHP) was used as a tool to combine the different hazard maps into an integrated hazard map. From the results, comparing the increase in the very high hazard area between the integrated hazard maps of the far future under the RCP2.6 and RCP4.5 scenarios, Khammouan Province has the highest increase (16.45 %). Additionally, the very high hazard area in Khammouan Province increased by approximately 12.47 % between the integrated hazard maps under the RCP4.5 and RCP8.5 scenarios of the far future. The integrated hazard maps can pinpoint the dangerous area through the whole country, and the map can be used as primary data for selected future development areas. There are some limitations of the AHP methodology, which supposes linear independence of alternatives and criteria.

Improved algorithm for matched-pairs selection of informative features in the problems of recognition of complex system states

The problem of computer diagnostics of complex systems is one of the non-trivial tasks of modern information technology. Such systems are, for example, computer networks, automatic and/or automated control systems for complex technological objects, including related to complex problems of environmental protection, biology, etc. In pattern recognition, one of the major problems is forming subspaces of informative features, which only in the «ensemble» allow diagnosing the states of such systems with a high degree of reliability. An effective approach to solving this problem based on the principles of inductive modeling of complex systems is proposed. The quality criterion for recognizing classes of patterns is formulated, which also makes it possible to evaluate the quality of the constructed ensemble of informative features. As an example, the problem of constructing an ensemble of informative features represented by a binary code based on the data of an experiment to determine the hazard levels of some plant protection products is considered. Real primary data on plant protection products used in practice were applied to recognize the effect of certain characteristics on the so-called integrated «hazard indicator». Comparative numerical estimates of the effectiveness of the proposed approach are given. In this case, there can be a fivefold gain in the amount of computations for a relatively small number of input features equal to 5 compared to the known algorithms of the class considered in the paper. It is shown that, from a practical point of view, the described algorithm has advantages over the known algorithms with brute-force search of feature subspaces in pattern recognition problems.

Using out-of-sample Cox–Snell residuals in time-to-event forecasting

The problem of assessing out-of-sample forecasting performance of event-history models is considered. Time-to-event data are usually incomplete because the event of interest can happen outside the period of observation or not happen at all. In this case, only the shortest possible time is observed and the data are right censored. Traditional accuracy measures like mean absolute or mean squared error cannot be applied directly to censored data, because forecasting errors also remain unobserved. Instead of mean error measures, researchers use rank correlation coefficients: concordance indices by Harrell and Uno and Somers’ Delta. These measures characterize not the distance between the actual and predicted values but the agreement between orderings of predicted and observed times-to-event. Hence, they take almost “ideal” values even in presence of substantial forecasting bias. Another drawback of using correlation measures when selecting a forecasting model is undesirable reduction of a forecast to a point estimate of predicted value. It is rarely possible to predict the timing of an event precisely, and it is reasonable to consider the forecast not as a point estimate but as an estimate of the whole distribution of the variable of interest. The article proposes computing Cox–Snell residuals for the test or validation dataset as a complement to rank correlation coefficients in model selection. Cox–Snell residuals for the correctly specified model are known to have unit exponential distribution, and that allows comparison of the observed out-of-sample performance of a forecasting model to the ideal case. The comparison can be done by plotting the estimate of integrated hazard function of residuals or by calculating the Kolmogorov distance between the observed and the ideal distribution of residuals. The proposed approach is illustrated with an example of selecting a forecasting model for the timing of mortgage termination.

Improvement of OSH Management through the holistic approach of incident controlling

This paper deals with the performance optimization of occupational safety and health management (OSHM) with the help of the integration of near miss management into existing KPIs of the company. In this context, two independent processes are carried out: risk assessment and near miss management. In this work, the holistic view of these two processes is investigated as an optimization potential OSHM. Based on a literature review, the framework of the qualitative method applied here is established. After definitions and general information concerning OSHM, the processes of risk assessment and near miss management in different organisations (23 international plants for risk assessment and 6 German plants for near miss management) with established processes according to BPM are examined. The chosen approach is combined with the method of the PDCA cycle to relate the results of the investigation to the CIP existing in the OSHM. The result was elaborated in the form of a recommendation for action: optimization of existing processes, integrated hazard and near miss management as a more sustainable solution and proposal for the implementation of a KPI for better control of incidents based on predictive risk assessment.

Environmental impact of long-term construction objects on urban systems

The significance of unfinished building object as elements of urban systems of modern Russian cities is shown. The existence of these objects can impact on urban environment conditions at a significant distance from the places where they are located. The urban environment is considered as a dynamically developing urban system, which includes a combination of potential-controlled natural and technical systems. The appearance of areas of uncontrolled environmental degradation around objects under incomplete construction reduces the level of comfort of urban environment. The main types of incomplete objects under construction and their impact on the environment are given. The article is based on observations of the state of more than 30 objects under construction and on the results of studies of environmental processes at the areas where they are located. The classification of objects under construction is proposed. The classification takes into account the stages of destruction of objects under construction and related environmental impacts. The need for a integrated hazard assessment of long-term construction objects as unmanageable degrading natural and technical systems is justified.

Integrated evaluation of water-related disasters using the analytical hierarchy process under land use change and climate change issues in Laos

In the past few decades, various natural hazards have occurred in Laos. To lower the consequences and losses caused by hazardous events, it is important to understand the magnitude of each hazard and the potential impact area. The main objective of this study was to propose a new approach to integrating hazard maps to detect hazardous areas on a national scale, for which area-limited data are available. The integrated hazard maps were based on a merging of five hazard maps: floods, land use changes, landslides, climate change impacts on floods and climate change impacts on landslides. The integrated hazard map consists of 6 maps under 3 representative concentration pathway (RCP) scenarios and 2 time periods (near future and far future). The analytical hierarchy process (AHP) was used as a tool to combine the different hazard maps into an integrated hazard map. From the results, comparing the increase in the very high-hazard area between the integrated hazard maps of the far future under the RCP2.6 and RCP4.5 scenarios, Khammouan Province has the highest increase (16.45 %). Additionally, the very high-hazard area in Khammouan Province increased by approximately 12.47 % between the integrated hazard maps under the RCP4.5 and 8.5 scenarios of the far future.

Risk assessment to curb COVID-19 contagion: A preliminary study using remote sensing and GIS

Globally, COVID-19 pandemic has become a threat to humans and to the socio-economic systems they have developed since the industrial revolution. Hence, governments and stakeholders are calling for strategies that could help to restore the normalcy while dealing with this pandemic effectively. Since, till now, the disease is yet to have a cure; therefore, only risk-based decision-making can help governments to achieve a solution that is sustainable in the long term. To help the decision-makers to explore viable actions, we here propose a risk assessment framework for analyzing COVID-19 risk to areas, using integrated hazard and vulnerability components associated with this pandemic for effective risk mitigation. The study is carried on a region administrated by Jaipur municipal corporation (JMC), India. Based on the current understanding of this disease, we hypothesized different COVID-19 risk indices (C19Ri) of the wards of JMC such as proximity to hotspots, total population, population density, availability of clean water and associated land use/ land cover, are related with COVID-19 contagion and calculated them in a GIS-based multi-criteria risk reduction method. The results showed disparateness in COVID-19 risk areas with higher risk in north-eastern and south-eastern zone wards within the boundary of JMC. We proposed to prioritize wards that are under higher risk zones for intelligent decision-making regarding COVID-19 risk reduction through appropriate management of resources-related policy consequences. This study aims to serve as a baseline study to be replicated in other parts of the country or world to eradicate the threat of COVID-19 effectively.

Escalating risk and pronounced inter-regional differences in exposure to natural hazards due to development patterns in the United States

<p>Combined, earthquakes, fires, floods, tornados and hurricanes are the most prominent natural disturbances in the United States that endanger human lives and result in substantial costs to society. Between 2006 and 2016, property and crop damage due to these hazards increased from ~5.4 to ~ 14.6 billion USD, with the record number of billion-dollar losses set in 2017. Unprecedented impacts and escalating costs highlight the imperative for better understanding of risk, which emerges from the coupling of disturbance probability and the exposure and adaptive capabilities of local communities. This study harmonizes earthquake, fire, flood, tornado and hurricanehazard data with fine-resolution annual settlement information to assess how risk due to changes in exposure has varied over the past 40 years across the contiguous U.S.Natural hazard risk assessments have been historically hindered by scale mismatches, poor characterization of property exposure and spatially-variable accuracy of the built environment. To overcome these limitations, we combined hazard occurrence data to create an integrated hazard map and employed gridded settlement layers from the Historical Settlement Data Compilation for the U.S. (HISDAC-US) derived from cadastral and housing data compiled in the Zillow Transaction and Assessment Dataset (ZTRAX) to map exposure. HISDAC-US describes the built environment of most of the country back to 1810 at fine temporal and spatial granularity. Trends in density of structures and built-up land were estimated for hazardous and non-hazardous areas (i.e., top and bottom 10% highest and lowest probabilities of a given hazard, respectively) as well temporal dynamics of risk at the subregional-, regional- and continental-scales.  Results suggest a monotonic increase in risk to all hazards as well as pronounced and rising spatial variability in exposure, pointing to long-standing institutional issues around equity and social justice. By assessing exposure at fine spatial resolution, with high temporal accuracy, and over long periods, we reliably identified populations at risk, and evaluated the development trajectories that lead to higher vulnerability to natural hazards.</p>