Combined forecasting model with CEEMD-LCSS reconstruction and the ABC-SVR method for landslide displacement prediction

Zhang, Junrong; Tang, Huiming; Tannant, Dwayne D.; Lin, Chengyuan; Xia, Ding; Liu, Xiao; Zhang, Yongquan; Ma, Junwei

doi:10.1016/j.jclepro.2021.126205

Cited by 54 publications

(25 citation statements)

References 43 publications

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“…In the present study, 124 measurements from October 2006 to January 2017 were used as the training set for the prediction model, and 21 measurements from February 2017 to October 2018 were treated as testing data. According to previous research on landslide displacement prediction [46,47], the trend components are mainly controlled by internal geological conditions and can be perfectly predicted by polynomial regression fitting. In contrast, the periodic component is mainly controlled by external triggering factors, such as rainfall intensity and reservoir fluctuation.…”

Section: Individual Predictionmentioning

confidence: 99%

A Novel Decomposition-Ensemble Learning Model Based on Ensemble Empirical Mode Decomposition and Recurrent Neural Network for Landslide Displacement Prediction

Niu

Wang

et al. 2021

Applied Sciences

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As vital comments on landslide early warning systems, accurate and reliable displacement prediction is essential and of significant importance for landslide mitigation. However, obtaining the desired prediction accuracy remains highly difficult and challenging due to the complex nonlinear characteristics of landslide monitoring data. Based on the principle of “decomposition and ensemble”, a three-step decomposition-ensemble learning model integrating ensemble empirical mode decomposition (EEMD) and a recurrent neural network (RNN) was proposed for landslide displacement prediction. EEMD and kurtosis criteria were first applied for data decomposition and construction of trend and periodic components. Second, a polynomial regression model and RNN with maximal information coefficient (MIC)-based input variable selection were implemented for individual prediction of trend and periodic components independently. Finally, the predictions of trend and periodic components were aggregated into a final ensemble prediction. The experimental results from the Muyubao landslide demonstrate that the proposed EEMD-RNN decomposition-ensemble learning model is capable of increasing prediction accuracy and outperforms the traditional decomposition-ensemble learning models (including EEMD-support vector machine, and EEMD-extreme learning machine). Moreover, compared with standard RNN, the gated recurrent unit (GRU)-and long short-term memory (LSTM)-based models perform better in predicting accuracy. The EEMD-RNN decomposition-ensemble learning model is promising for landslide displacement prediction.

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Section: Individual Predictionmentioning

confidence: 99%

A Novel Decomposition-Ensemble Learning Model Based on Ensemble Empirical Mode Decomposition and Recurrent Neural Network for Landslide Displacement Prediction

Niu

Wang

et al. 2021

Applied Sciences

Self Cite

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“…With an increase in indirect costs, the traditional model leads to an inadequate relationship between them. Unable to establish a cause and effect relationship between cost and resources, leading to the need for further exploration by other methods [25].…”

Section: Synthesis Of the Subjectmentioning

confidence: 99%

Model of indirect Expenses Distribution for Determining Economies of Scale

2021

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Changing economic environment, innovative production technologies and the need to obtain relevant information in decisionmaking, management determines the organizations to seek different approaches to identify economies of scale. Economies of scale are manifested as an effect of cost reduction. The article proposes a comparative analysis of two methods of establishing costs that allow the identification and quantification of economies of scale. The research proposes a distribution of indirect costs depending on the cause-effect relationship between activity and product. The research results show a cost difference in the case of implementing the Activity-based costing (ABC) cost system, thus recognizing the usefulness and compatibility of the method.

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“…Los frecuentes peligros geológicos en todo el mundo vienen causando pérdidas económicas significativas por deslizamientos de tierras en áreas montañosas y, en áreas bajas, por desplazamiento de la corriente de agua y lodo provocados por precipitaciones o cambios estacionales en el nivel de los embalses, con efectos directos a áreas de cultivo que, a pesar de conocimiento local, no es posible evitarlo, traduciéndose en consecuencias ambientales negativas en los cuerpos acuáticos y tierras de cultivo (Argota Pérez et al, 2020;Pham et al, 2021). Frente a ello, el sistema ABC fue una de las mejores opciones para calcular costos reales tanto en la prevención como en la reconstrucción de tierras para evaluar su rentabilidad: Cada proceso secuencial de deslizamiento de agua y lodo hacia tierras abajo (producto de lluvias que no solo inundan cultivos y pasturas sino también afectan los ductos de cables eléctricos, cañerías de agua, gas, alcantarillas y otros) podrían provocar lesiones a la salubridad ambiental y de salud humana, por lo que requieren ser valorizados económicamente, acumulando desembolsos monetarios para determinar los costos promedios de cada proceso; allí fue implementado el sistema ABC como una opción efectiva de prevención y reparación (Zhang et al, 2021).…”

Section: Deslizamientos De Tierras Agrícolasunclassified

Activity-based costing (ABC) in SMEs and innovative initiatives: possible option or expired?

Mamani

Argota-Pérez²,

Nina

et al. 2021

Rev. Investig. Altoandin.

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The quantification of production/service costs to determine the market price is fundamental in offering the maximum value of satisfaction. Therefore, management accounting is essential. One of the alternative tools is activity-based costing, known as ABC system, an alternative method to overcome the limitations of traditional indirect cost systems, which somehow distort the actual accounting of costs. Will exploring its development, applicability, challenges and benefits still be a possible option? This study aimed at reviewing the scientific literature produced on the activity-based costing system in recent years, identifying trends of adoption and challegnes of implementation in various manufacturing and service firms. High impact journals indexed in PubMed, Web of Science (WoS), Scopus, among others, were analyzed. The results show an increase of publications on the implementation of the ABC system in PubMed (855 publications), WoS (1131) and Scopus (2535). The results show that its applicability remains a possible option as an alternative costing tool for SME managers or owners. This study concludes that the application of the ABC system is adequate to determine real costs and could guarantee more reasonable and competitive prices in the market. However, there is still resistance to its implementation due to human and technological ignorance.

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Combined forecasting model with CEEMD-LCSS reconstruction and the ABC-SVR method for landslide displacement prediction

Cited by 54 publications

References 43 publications

A Novel Decomposition-Ensemble Learning Model Based on Ensemble Empirical Mode Decomposition and Recurrent Neural Network for Landslide Displacement Prediction

A Novel Decomposition-Ensemble Learning Model Based on Ensemble Empirical Mode Decomposition and Recurrent Neural Network for Landslide Displacement Prediction

Model of indirect Expenses Distribution for Determining Economies of Scale

Activity-based costing (ABC) in SMEs and innovative initiatives: possible option or expired?

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