A combination of expert-based system and advanced decision-tree algorithms to predict air-overpressure resulting from quarry blasting
- He, Ziguang, Armaghani, Danial, Masoumnezhad, Mojtaba, Khandelwal, Manoj, Zhou, Jian, Murlidhar, Bhatawdekar
- Authors: He, Ziguang , Armaghani, Danial , Masoumnezhad, Mojtaba , Khandelwal, Manoj , Zhou, Jian , Murlidhar, Bhatawdekar
- Date: 2021
- Type: Text , Journal article
- Relation: Natural Resources Research Vol. 30, no. 2 (2021), p. 1889-1903
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- Description: This study combined a fuzzy Delphi method (FDM) and two advanced decision-tree algorithms to predict air-overpressure (AOp) caused by mine blasting. The FDM was used for input selection. Thus, the panel of experts selected four inputs, including powder factor, max charge per delay, stemming length, and distance from the blast face. Once the input selection was completed, two decision-tree algorithms, namely extreme gradient boosting tree (XGBoost-tree) and random forest (RF), were applied using the inputs selected by the experts. The models are evaluated with the following criteria: correlation coefficient, mean absolute error, gains chart, and Taylor diagram. The applied models were compared with the XGBoost-tree and RF models using the full set of data without input selection results. The results of hybridization showed that the XGBoost-tree model outperformed the RF model. Concerning the gains, the XGBoost-tree again outperformed the RF model. In comparison with the single decision-tree models, the single models had slightly better correlation coefficients; however, the hybridized models were simpler and easier to understand, analyze and implement. In addition, the Taylor diagram showed that the models applied outperformed some other conventional machine learning models, including support vector machine, k-nearest neighbors, and artificial neural network. Overall, the findings of this study suggest that combining expert opinion and advanced decision-tree algorithms can result in accurate and easy to understand predictions of AOp resulting from blasting in quarry sites. © 2020, International Association for Mathematical Geosciences.
- Authors: He, Ziguang , Armaghani, Danial , Masoumnezhad, Mojtaba , Khandelwal, Manoj , Zhou, Jian , Murlidhar, Bhatawdekar
- Date: 2021
- Type: Text , Journal article
- Relation: Natural Resources Research Vol. 30, no. 2 (2021), p. 1889-1903
- Full Text:
- Reviewed:
- Description: This study combined a fuzzy Delphi method (FDM) and two advanced decision-tree algorithms to predict air-overpressure (AOp) caused by mine blasting. The FDM was used for input selection. Thus, the panel of experts selected four inputs, including powder factor, max charge per delay, stemming length, and distance from the blast face. Once the input selection was completed, two decision-tree algorithms, namely extreme gradient boosting tree (XGBoost-tree) and random forest (RF), were applied using the inputs selected by the experts. The models are evaluated with the following criteria: correlation coefficient, mean absolute error, gains chart, and Taylor diagram. The applied models were compared with the XGBoost-tree and RF models using the full set of data without input selection results. The results of hybridization showed that the XGBoost-tree model outperformed the RF model. Concerning the gains, the XGBoost-tree again outperformed the RF model. In comparison with the single decision-tree models, the single models had slightly better correlation coefficients; however, the hybridized models were simpler and easier to understand, analyze and implement. In addition, the Taylor diagram showed that the models applied outperformed some other conventional machine learning models, including support vector machine, k-nearest neighbors, and artificial neural network. Overall, the findings of this study suggest that combining expert opinion and advanced decision-tree algorithms can result in accurate and easy to understand predictions of AOp resulting from blasting in quarry sites. © 2020, International Association for Mathematical Geosciences.
Estimating visual quality, a component of culturally-associated ecosystem services in palaeo-lake environments
- Chhetri, Prem, Kattel, Giri, Dong, Xuhui, Yang, Xiangdong, Min, Xu
- Authors: Chhetri, Prem , Kattel, Giri , Dong, Xuhui , Yang, Xiangdong , Min, Xu
- Date: 2014
- Type: Text , Conference paper
- Relation: Symposium on Australia-China Wetland Network Research Partnership; Nanjing Institute of Geography and Limnology Chinese Academy of Sciences (NIGLAS) Nanjing, China; 23rd-28th December 2014 p. 23-26
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- Description: Evaluation of visual quality is essentially a multi-dimensional and multi-sensory experience of landscape assessment. Visual quality refers to the character, condition and quality of lakes/wetlands. It involves perceiving, preferring and valuing the visual quality by the public. Visual quality is an outcome of the perceptual, cognitive and emotional processes in response to visual stimuli of a lake environment. Visual quality therefore is dependent upon the perceptual and structural aspects of perceived scenes of wetlands. Visual assessment, an evaluating process of gaining non-material or intangible benefits by people from ecosystems, through spiritual enrichment, cognitive development, self-reflection, recreation, and aesthetic experiences, has now become one of significant research areas under cultural components of ecosystem services. Public perception in such studies is composed from both the objective and subjective elements of human–landscape interactions. However, it is still a matter of debate whether subjective–objective realities are dichotomous or supplementary to enhancing the quality of human experiences in natural settings. In fact, much research considers them as inseparable and integral parts of landscape perception, despite the tendency for disintegrating landscapes into their constituent components. There is a fundamental theoretical divergence of opinions over the question whether a landscape has an intrinsic or ‘objective’ beauty, which may be in some ways measurable or comparable, or whether beauty is a value that can be only attributed subjectively to an area or a specific landscape.
- Authors: Chhetri, Prem , Kattel, Giri , Dong, Xuhui , Yang, Xiangdong , Min, Xu
- Date: 2014
- Type: Text , Conference paper
- Relation: Symposium on Australia-China Wetland Network Research Partnership; Nanjing Institute of Geography and Limnology Chinese Academy of Sciences (NIGLAS) Nanjing, China; 23rd-28th December 2014 p. 23-26
- Full Text:
- Reviewed:
- Description: Evaluation of visual quality is essentially a multi-dimensional and multi-sensory experience of landscape assessment. Visual quality refers to the character, condition and quality of lakes/wetlands. It involves perceiving, preferring and valuing the visual quality by the public. Visual quality is an outcome of the perceptual, cognitive and emotional processes in response to visual stimuli of a lake environment. Visual quality therefore is dependent upon the perceptual and structural aspects of perceived scenes of wetlands. Visual assessment, an evaluating process of gaining non-material or intangible benefits by people from ecosystems, through spiritual enrichment, cognitive development, self-reflection, recreation, and aesthetic experiences, has now become one of significant research areas under cultural components of ecosystem services. Public perception in such studies is composed from both the objective and subjective elements of human–landscape interactions. However, it is still a matter of debate whether subjective–objective realities are dichotomous or supplementary to enhancing the quality of human experiences in natural settings. In fact, much research considers them as inseparable and integral parts of landscape perception, despite the tendency for disintegrating landscapes into their constituent components. There is a fundamental theoretical divergence of opinions over the question whether a landscape has an intrinsic or ‘objective’ beauty, which may be in some ways measurable or comparable, or whether beauty is a value that can be only attributed subjectively to an area or a specific landscape.
Is what you see what you get? Visual vs. measured assessments of vegetation condition
- Cook, Carly, Wardell-Johnson, Grant, Keatley, Marie, Gowans, Stacey, Gibson, Matthew, Westbrooke, Martin, Marshall, Dustin
- Authors: Cook, Carly , Wardell-Johnson, Grant , Keatley, Marie , Gowans, Stacey , Gibson, Matthew , Westbrooke, Martin , Marshall, Dustin
- Date: 2010
- Type: Text , Journal article
- Relation: Journal of Applied Ecology Vol. 47, no. 3 (2010), p. 650-661
- Full Text: false
- Reviewed:
- Description: 1. An important step in the conservation of biodiversity is to identify what exists, its quantity and its quality (i.e. condition). This can be a daunting task at the landscape-scale, so vegetation communities are often used as surrogates for biodiversity. Satellite imagery has improved our ability to rapidly measure vegetation parameters but the need for calibration still requires rapid and cost-effective on-ground condition assessment. Some management agencies address this need by using visual condition assessments, with unknown consequences for the different purposes of condition data. It is therefore vital to examine the comparability of visual and systematic condition assessment methods to guide their use in conservation decision making. 2. We compared visual assessments of vegetation condition with more systematic and higher resolution on-ground assessments, using a method where both assessments were made for the same quadrats. We determined both the condition parameters observers respond to when making visual assessments of condition, and the consequences of any differences for the application of these data. 3. We found that visual assessment of vegetation condition broadly represented measured assessments of the same vegetation, but that observers simplify their assessments by responding to only some of the measured condition parameters. No consistent trends were found in the parameters observers responded to across the different vegetation types sampled. 4. Synthesis and applications. We conclude that visual estimates of vegetation condition are only of sufficient resolution to replace more expensive, high-resolution assessments at a landscape-scale, when condition results are combined over multiple areas and vegetation types. Visual assessment methods potentially can provide an efficient measure of overall condition for conservation management agencies where practitioners can make assessments of condition in the course of their daily management activities - an important step forward. At smaller scales, idiosyncratic effects render visual estimates highly variable when compared with systematic condition assessments. This variability, especially among vegetation types, suggests that more systematic assessments are necessary when management decisions require higher-resolution estimates of changes in individual condition parameters, such as when measuring the success of individual management actions. These findings provide a valuable guide for selecting the most appropriate approach for the different objectives of condition assessments for biodiversity conservation.
- Description: 2003008171
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