Integrated Uncertainty in Knowledge Modelling and Decision Making (eBook, PDF)

8th International Symposium, IUKM 2020, Phuket, Thailand, November 11-13, 2020, Proceedings
Redaktion: Huynh, Van-Nam; Yenradee, Pisal; Inuiguchi, Masahiro; Jeenanunta, Chawalit; Entani, Tomoe

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 8th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2020, held in Phuket, Thailand, in November 2020.*

The 35 full papers presented were carefully reviewed and selected from 55 submissions. The papers deal with all aspects of uncertainty modelling and management and are organized in topical sections on uncertainty management and decision support; machine learning; machine learning applications; econometric applications; and statistical methods.

* The conference was held virtually due to the COVID-19 pandemic.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 432
• Erscheinungstermin: 2. November 2020
• Englisch
• ISBN-13: 9783030625092
• Artikelnr.: 62292425

Inhaltsangabe

Uncertainty Management and Decision Support.- Outcome Range Problem in Interval Linear Programming: An Exact Approach.- Weak and Strong Consistency of an Interval Comparison Matrix.- The Facility Location Problem with a Joint Probabilistic Constraint.- The Advantage of Interval Weight Estimation over the Conventional Weight Estimation in AHP in Ranking Alternatives.- Decision Support Framework for Composing of Different Questionnaires based on Business Model with Optimization.- Algorithms for Generating Sets of Gambles for Decision Making with Lower Previsions.- PM 2.5 Problem in Chiang Mai, Thailand: The Application of Maximizing Expected Utility with Imbalanced Loss Functions.- Identification of the Direct and Indirect Drivers of Deforestation and Forest Degradation in Cambodia.- Unit Commitment Problem in the Deregulated Market.- Risk Impact Assessment and Prioritization in Multimodal Freight Transportation Systems.- Machine Learning.- Dynamic Features Spaces and Machine Learning: Open Problems and Synthetic Data Sets.- An Evidential Reasoning Framework for User Profiling Using Short Texts.- Basic Consideration of Co-clustering Based on Rough Set Theory.- Rank Estimators for Robust Regression: Approximate Algorithms, Exact Algorithms and Two-stage Methods.- A New Classification Technique Based on The Combination of Inner Evidence.- SOM-Based Visualization of Potential Technical Solutions with Fuzzy Bag-of-Words Utilizing Multi-view Information.- Machine Learning Applications.- Relative Humidity Estimation Based on Two Nested Kalman Filters with Bicubic Interpolation for Commercial Cultivation of Tropical Orchids.- Customized Dynamic Pricing for Air Cargo Network via Reinforcement Learning.- Analysis of the Determinants of CO2 Emissions: A Bayesian LASSO Approach.- Comparison Between Original Texts and Their Revisions to Improve Foreign Language Writing.- Motion Time Study with Convolutional Neural Network.- Unsupervised Change Detectionin Multi-temporal Satellite Images Based on Structural Patch Decomposition and k-means Clustering for Landslide Monitoring.- Nowcasting and Forecasting for Thailand's Macroeconomic Cycles Using Machine Learning Algorithms.- Econometric Applications.- Dependence of Financial Institutions in China: An Analysis Based on FDG Copula Model.- Evaluation and Forecasting of Functional Port Technical Efficiency in ASEAN-4.- A Spatial Analysis of International Tourism Demand Model: the Exploration of ASEAN Countries.- Measurements of the Conditional Dependence Structure Among Carbon, Fossil Energy and Renewable Energy Prices: Vine Copula Based GJR-GARCH Model.- Prediction of Closing Stock Prices using the Artificial Neural Network in the Market for Alternative Investment (MAI) of the Stock Exchange of Thailand (SET).- Estimating Fish Dispersal using Interval Estimations for the Single Variance of a Delta-Lognormal Distribution.- Statistical Methods.- Bayesian Confidence Intervals for Means of Normal Distributions with Unknown Coefficients of Variation.- Confidence Intervals for the Difference between the Coefficients of Variation of Inverse Gaussian Distributions.- Methods for Testing the Difference between Two Signal-To-Noise Ratios of Log-Normal Distributions.- Generalized Confidence Interval of the Ratio of Coefficients of Variation of Birnbaum-Saunders Distribution.- Confidence Interval for Coefficient of Variation of Inverse Gamma Distributions.- The Bayesian Confidence Interval for the Mean of the Zero-inflated Poisson Distribution.