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1. Sustainable Directions in Tourism.

Author

Espino-Rodríguez, Tomás

Subjects
A'WOT, Apuseni mountains, China, ICT, LSTM model, PM10, TOWS matrix, agritourism, air pollution, all-for-one tourism, behavioral intentions, campsites, certification, choice experiment, climate change, cluster analysis, community-based tourism, compartmentalisation, constraint, deep learning framework, destination development, discrete choice experiments, ecolabel, ecolabel adoption, electricity, essential marketing, event quality, forecast through a logistic model, forecasting, forecasting performance, hotel accommodation demands, hotel industry, hotel management, inbound tourism, internet search index, invasive species control, islands, learning-based tourism, local community, motivation, mountain areas, museum planning, negative externalities, physical environment (PhE), place attachment, pro-social/pro-environmental behavior, purchasing, qualitative methodology, regional disparity, regression discontinuity design, science museum, semantic analysis, sense of belonging, spatial analysis, sport tourism, sporting event, strategic planning, supply chain, sustainability, sustainability services marketing matrix, sustainable daily practices, sustainable development, sustainable tourism, the "health" of rural settlements, time series, tourism, tourism and sustainability, tourism evaluation, tourism indicators, tourist satisfaction, tourists' preferences, two stage on-site sampling, value and tourism, visitor behavior, visitor satisfaction, young adults
Abstract

Summary: Within the framework of tourism companies and tourist destinations, the question of sustainability is gaining importance. Tourists are increasingly aware of the importance of sustainability criteria, awarding greater value to sustainable destinations. Sustainability refers to a wide range of aspects related to climate change, the economic organization of tourism, social values or questions, job creation, and the necessary protection of the culture of destinations and the environment. Therefore, there is a need for studies that consider these aspects in order to achieve the sustainable development of tourist destinations. Fundamental to this is discovering to what degree tourism companies and destinations approach these questions in the strategies they use to deal with problems stemming from their attempts to be more sustainable. Conceptual papers and empirical research on the economic, social, cultural, and environmental aspects related to tourism companies and destinations are welcome. Studies that analyze how these questions and the concept of sustainability are included in tourism companies and destinations are necessary in these modern times. This book was established for these reasons, dedicated to examining sustainability in tourism. The papers included in this Special Issue can help us to determine the new directions being addressed in the research on sustainability tourism.

2. Quantitative Methods for Economics and Finance.

Author

Trinidad-Segovia, J.E., Sánchez-Granero, Miguel Ángel, and Trinidad-Segovia, J.E.

Subjects
Coins, banknotes, medals, seals (numismatics), Bitcoin, Chinese listed companies, DCC, DEA, EGARCH, EVT, Ethereum, FD4 approach, GARCH, Hurst exponent, Markov Chain Monte Carlo simulation, P 500, P500, Ripple, S&amp, SRA approach, Tobin's q, United States, VaR, academic cheating, asset pricing, autoregressive integrated moving average (ARIMA), bilateral investment treaties, biotechnological firms, bitcoin, cash flow management, centered model, co-movement, cointegration, commodity prices, computational finance, copula, copulas, corporate prudential risk, correlation risk premium, cryptocurrency, decision-making process, decreasing impatience, deep learning, deep recurrent convolutional neural networks, delay, derivation, detection, discount, dispersion trading, dynamically simulated autoregressive distributed lag (DYS-ARDL), econometrics, eigenvalues, elasticity, energy consumption, ensemble empirical mode decomposition (EEMD), essential multicollinearity, financial distress, financial distress prediction, financial markets, forecasting, foreign direct investment, futures prices, generalized Pareto distribution, genetic algorithm (GA), gold, historical simulation approach, hurst exponent, induced risk aversion, informality, intercept, intertemporal choice, liquidity constraints, liquidity risk, local optima vs. local minima, long memory, macroeconomic propagation, mean square error, multicollinearity, multiperiod financial management, multiple periods, non-linear macroeconomic modelling, non-parametric efficiency, noncentered model, nonessential multicollinearity, number of factors, option arbitrage, pairs trading, peaks-over-threshold, pharmaceutical industry, policy uncertainty, precautionary savings, probability, probability of volatility cluster, productivity, profitability, raise regression, regional trade agreements, risk, scale economies, stock prices, structural gravity model, student t-copula, support vector regression (SVR), tax evasion, the financial accelerator, threshold regression, unconstrained distributed lag model, variance inflation factor, volatility cluster, volatility series, volatility trading
Abstract

Summary: This book is a collection of papers for the Special Issue "Quantitative Methods for Economics and Finance" of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice.

3. Assessment of Renewable Energy Resources with Remote Sensing.

Author

Martins, Fernando Ramos and Martins, Fernando Ramos

Subjects
Research & information: general, Baltic area, CSP plants, GES-CAL software, Hazaki Oceanographical Research Station, artificial neural networks, climate, cloud, cloud coverage, cloud detection, coastal wind measurements, coastline, computational design method, convection, data processing, digitized image processing, electrical resistivity tomography, extreme value analysis, feature engineering, feature importance, forecasting, geophysical prospecting, geothermal energy, global radiation, graphical user interface software, hydropower reservoir, image processing, lake breeze influence, light gradient boosting machine, machine learning, machine learning techniques, metaheuristic, multistep-ahead prediction, parameter extraction, passive design strategy, photovoltaic power plant, plan position indicator, point cloud data, potential well field location, remote sensing, remote sensing data acquisition, renewable energy resource assessment and forecasting, satellite, scanning LiDAR, scatterometer, shading envelopes, sky camera, smart island, solar energy, solar energy resource, solar irradiance enhancement, solar irradiance estimation, solar irradiance forecasting, solar photovoltaic, solar radiation forecasting, statistical analysis, surface solar radiation, time domain electromagnetic method, total sky imagery, velocity volume processing, voxel-design approach, whale optimization algorithm, wind speed
Abstract

Summary: The book "Assessment of Renewable Energy Resources with Remote Sensing" focuses on disseminating scientific knowledge and technological developments for the assessment and forecasting of renewable energy resources using remote sensing techniques. The eleven papers inside the book provide an overview of remote sensing applications on hydro, solar, wind and geothermal energy resources and their major goal is to provide state of art knowledge to contribute with the renewable energy resource deployment, especially in regions where energy demand is rapidly expanding. Renewable energy resources have an intrinsic relationship with local environmental features and the regional climate. Even small and fast environment and/or climate changes can cause significant variability in power generation at different time and space scales. Methodologies based on remote sensing are the primary source of information for the development of numerical models that aim to support the planning and operation of an electric system with a substantial contribution of intermittent energy sources. In addition, reliable data and knowledge on renewable energy resource assessment are fundamental to ensure sustainable expansion considering environmental, financial and energetic security.

4. Bayesian Econometrics.

Author

Bernardi, Mauro, Bernardi, Mauro, Grassi, Stefano, and Ravazzolo, Francesco

Subjects
Technology: general issues, Bayesian TVP-SV-VAR, Bayesian VAR, Bayesian econometrics, Bayesian estimation, Bayesian nonlinear mixed-effects regression, Bitcoin, CES function, DSGE model, ES, MCMC methods, cryptocurrency, density forecast, density forecasting, dynamic model averaging, dynamic model selection, fiscal policy, forecasting, forgetting factors, macroeconomic and financial applications, military and civilian spending, monetary policy, point forecast, portfolio choice, sentiments, stock market predictability, time-varying volatility, transmission channel, unconventional monetary policy
Abstract

Summary: Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data, models, parameters and parameter restriction uncertainties, in a unified and coherent framework. This book contributes to this literature by collecting a set of carefully evaluated contributions that are grouped amongst two topics in financial economics. The first three papers refer to macro-finance issues for real economy, including the elasticity of factor substitution (ES) in the Cobb-Douglas production function, the effects of government public spending components, and quantitative easing, monetary policy and economics. The last three contributions focus on cryptocurrency and stock market predictability. All arguments are central ingredients in the current economic discussion and their importance has only been further emphasized by the COVID-19 crisis.

5. The 8th International Conference on Time Series and Forecasting.

Author

Rojas, Ignacio, Herrera, Luis, Kaufman, Peter, Pomares, Hector, Rojas, Fernando, Rojas, Ignacio, and Valenzuela, Olga

Subjects
Computer science, Information technology industries, : financial market volatility, ARIMA, CNN, COVID-19, DCCA method, K-Means, K-mean clustering, LSTM, Markov chain, NARNN, VAR-DCC-GARCH, accessibility, all sky images, anomaly detection, cloud-base height, clustering, convolutional neural network, cross-correlation, diagnosis, dynamic convergence, dynamic mode decomposition with control, ecosystem respiration, energy, error diagnosis, faults, forecasting, health forecasting, hydrological data, intensive care unit (ICU), longshort-term memory (LSTM), machine learning, machine learning (ML), machinelearning, mobile data traffic, model evaluation, multivariate prediction, non-stationary time series, oil derivatives, oil production, ordinal patterns, outlier detection, outlier detection in time series, prediction, prediction intervals, predictive maintenance, privacy, readmission prediction, recurrent neural network (RNN), retainability, seq2seq, shareable data, signal processing, spatial, spectrum, stationarity, structural breaks, synthetic data, temporal, time delay embedding, time series, time series analysis, time series cluster evaluation, time series clustering, time series data, time series forecasting, time-series, time-series forecasting, unit root, utilization, wavelet-based random forest, PV systems, automated machine learning
Abstract

Summary: The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation and use of new knowledge, computational techniques and methods on forecasting in a wide range of fields.

6. Sustainability Analysis and Environmental Decision-Making Using Simulation, Optimization, and Computational Analytics.

Author

Yeomans, Julian Scott, Kozlova, Mariia, and Yeomans, Julian Scott

Subjects
Mathematics & science, Research & information: general, C-vine copula, CO2 emissions, DEA, Germany, Iowa food-energy-water nexus, LASSO, Monte Carlo simulation, South Texas, biofuel policy, biomass gasification, boron, business aviation, classification, computer modeling, computer simulation, desalination, dynamic programming, eco-efficiency, ecological indicators, ecological relationship, electric motor, electricity production, energy modeling, energy system design, environmental footprint, factorial analysis, feature selection, feed-in tariff, financial market, forecasting, fuzzy, generation profile, input-output analysis, interval, investing, investment profitability analysis, joint dependencies, machine learning, model reduction, modelling, n/a, nitrogen export, nonpoint source pollution, operational flexibility, optimal allocation, optimal path, parameter estimation, point source pollution, pollutant loadings, quantile regression, reduction, regression, renewable energy, renewable energy support, reverse osmosis, seawater, simulation, simulation decomposition, sourcing, specific power, streamflow forecasting, sustainability, system modeling, the pay-off method, turboprop, unlisted companies, urban solid waste system, water quality, water resource management, water resources, watershed management, weather modeling
Abstract

Summary: Effective environmental decision-making is often challenging and complex, where final solutions frequently possess inherently subjective political and socio-economic components. Consequently, complex sustainability applications in the "real world" frequently employ computational decision-making approaches to construct solutions to problems containing numerous quantitative dimensions and considerable sources of uncertainty. This volume includes a number of such applied computational analytics papers that either create new decision-making methods or provide innovative implementations of existing methods for addressing a wide spectrum of sustainability applications, broadly defined. The disparate contributions all emphasize novel approaches of computational analytics as applied to environmental decision-making and sustainability analysis - be this on the side of optimization, simulation, modelling, computational solution procedures, visual analytics, and/or information technologies.

7. Renewable Energy Resource Assessment and Forecasting.

Author

Galanis, George and Galanis, George

Subjects
Research & information: general, ANFIS, Granger causality, Kalman filtering, Kalman-Bayesian filter, Markov chains, WRF, anthropogenic waste processing, biofuel, biomass, biotechnology, central solar receiver, clearness coefficient, climate policy, complex terrain, concentrated solar, concentrating solar power, cross border trading, deep learning, deformable models, developing countries, different horizontal resolution, direct normal irradiance, economic efficiency, electric energy demand, electricity trading, energy, energy resource assessment, forecast, forecast errors, forecasting, functional statistics, global horizontal irradiance (GHI), heat supply of industrial processes, high-resolution, momentum sink, nowcasting, numerical weather prediction model, open channel flows, operational strategies, particle swarm optimization, photovoltaic solar energy, prediction, ramp rates, renewable energy, renewable energy forecasting, renewable energy sources, risk analysis, shape-invariant model, shark algorithm, shock-capturing capability, short-term forecasts, solar collectors, solar irradiance forecasts, solar irradiation, solar radiation, solar resource, spot prices, sustainable development, system advisor model, the European Green Deal, thermochemical, thrust force coefficient, tidal-stream energy, unbounded flow, validation, weather research and forecasting model, wind
Abstract

Summary: In recent years, several projects and studies have been launched towards the development and use of new methodologies, in order to assess, monitor, and support clean forms of energy. Accurate estimation of the available energy potential is of primary importance, but is not always easy to achieve. The present Special Issue on 'Renewable Energy Resource Assessment and Forecasting' aims to provide a holistic approach to the above issues, by presenting multidisciplinary methodologies and tools that are able to support research projects and meet today's technical, socio-economic, and decision-making needs. In particular, research papers, reviews, and case studies on the following subjects are presented: wind, wave and solar energy; biofuels; resource assessment of combined renewable energy forms; numerical models for renewable energy forecasting; integrated forecasted systems; energy for buildings; sustainable development; resource analysis tools and statistical models; extreme value analysis and forecasting for renewable energy resources.

8. Appropriate Wisdom, Technology, and Management toward Environmental Sustainability for Development.

Author

Hashemi, Shervin and Hashemi, Shervin

Subjects
Environmental science, engineering & technology, History of engineering & technology, Technology: general issues, Bangladesh, CO2, COVID-19, Clean Development Mechanism, Internet of Things (IoT), MENA Islamic cities, Mexico, PLS-SEM, SDGs, VECM, aquaculture, arsenic, benchmarking, biodiesel, blockchain, brand loyalty, circular economy, construction sector, construction waste reduction, consumer brand relationships, corrugated cardboard, cost-benefit analysis, crumb rubber, developing countries, disposal, dose-response, eco-friendly sound-absorbing material, economic reactivation, economy, emission reductions, emissions, engine performance, environmental regulations, ethical marketing, ethnobotany, extended marketing mix, fisheries, food security, forecasting, geometric mean weighting, green recovery, groundwater level, groundwater management models, groundwater monitoring system, groundwater resource, human health, humanitarian logistics, industry 4.0, innovation, intersectoral linkages, landfill, manufacturing supply chains, metals, modelling of waste (reduce, reuse and recycle), multi-frequency resonator, multiobjective linear programming, n/a, natural feedstocks, pandemic, penalty weighting, perforated corrugated cardboard, pollution, potential solutions, poverty, power plants, product life cycle cost, production method, response surface methodology, revised multichoice goal programming, rice husk, rural Gansu, rural clean heating project, scorecard, seed rate, seed recycling, self-compacting concrete, silica fume, sound transmission loss, sound-absorption coefficient, spatial modelling, strength, supplier selection, sustainability, sustainable agriculture, sustainable built environment, sustainable construction, sustainable development, sustainable development goals, traditional knowledge, transfer function method, transfer matrix method, urban management, urban solid waste, waste management, wheat, wireless sensor network, yield effect
Abstract

Summary: The protection and maintenance of environmental resources for future generations require responsible interaction between humans and the environment in order to avoid wasting natural resources. According to an ancient Native American proverb, "We do not inherit the Earth from our ancestors; we borrow it from our children." This indigenous wisdom has the potential to play a significant role in defining environmental sustainability. Recent technological advances could sustain humankind and allow for comfortable living. However, not all of these advancements have the potential to protect the environment for future generations. Developing societies and maintaining the sustainability of the ecosystem require appropriate wisdom, technology, and management collaboration. This book is a collection of 19 important articles (15 research articles, 3 review papers, and 1 editorial) that were published in the Special Issue of the journal Sustainability entitled "Appropriate Wisdom, Technology, and Management toward Environmental Sustainability for Development" during 2021-2022.addresses the policymakers and decision-makers who are willing to develop societies that practice environmental sustainability, by collecting the most recent contributions on the appropriate wisdom, technology, and management regarding the different aspects of a community that can retain environmental sustainability.

9. Frontiers of Asset Pricing.

Author

Kolari, James W., Kolari, James W., and Pynnonen, Seppo

Subjects
Philosophy, Bitcoin, GARCH-jump, Poisson model, S&P 500 index, abnormal returns, announcements, asset pricing, at-the-money, bias adjustments, carry cost rate, clustered event days, commodity market, conditional hedge ratio, cross-sectional correlation, cryptocurrencies, cumulated ranks, deep-out-of-the-money, direction, earnings, economics, efficient market hypothesis, efficient portfolios, event study, expectation-maximization (EM) regression, finance, forecasting, free-boundary problem, hedge ratio, informed trading, latent variable, market factor, market index, market volume, metals, momentum, multifactors, net buying pressure, options, out-of-the-money, outliers, pairs trading, portfolio profitability, pricing, rank test, return dispersion, risk factors, spectral analysis, standardized abnormal returns, stochastic control, survivor stocks, term structure, time-varying jumps, trading strategies, transaction costs, transaction regions, unit root, volatility, yield spread, zero-beta CAPM
Abstract

Summary: This book is comprised of articles published in a Special Issue of the Journal of Risk and Financial Management entitled "Frontiers in Asset Pricing" with Guest Editors Professor James W. Kolari and Professor Seppo Pynnonen. The book contains papers in various areas related to asset pricing: (1) models; (2) multifactors; (3) theory; (4) empirical tests; (5) applications; (6) other asset classes; and (7) international tests.

10. Increasing Energy Efficiency and Flexibility by Forecasting Production Energy Demand Based on Machine Learning

Author

Trenz, André, Hoffmann, Christoph, Lange, Christopher, Öchsner, Richard, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Haddar, Mohamed, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Kohl, Holger, editor, Seliger, Günther, editor, and Dietrich, Franz, editor

Published
2023
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11. Numerical and Statistical Probability Distribution Transformation for Modeling Traffic in Optical Networks

Author

Poturała, Alicja, Konieczka, Maria, Śliwka, Piotr, Sujecki, Sławomir, Kozdrowski, Stanisław, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Groen, Derek, editor, de Mulatier, Clélia, editor, Paszynski, Maciej, editor, Krzhizhanovskaya, Valeria V., editor, Dongarra, Jack J., editor, and Sloot, Peter M. A., editor

Published
2022
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13. Nowcasting Unemployment Rates with Smartphone GPS Data

Author

Moriwaki, Daisuke, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tserpes, Konstantinos, editor, Renso, Chiara, editor, and Matwin, Stan, editor

Published
2020
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14. Chapter Machine Learning-Based Construction Planning and Forecasting Model

Author

Keser, Ahmet Esat and Tokdemir, Onur Behzat

Subjects
Machine Learning, Planning, Scheduling, Forecasting, Data Visualizing, Construction, Business Intelligence, thema EDItEUR::U Computing and Information Technology
Abstract

Construction planning and scheduling are crucial aspects of project management that require a lot of time and resources to manage effectively. Machine learning and artificial intelligence techniques have shown great potential in improving construction planning and scheduling by providing more accurate insights into project progress and forecasting. This paper proposed a machine learning model that utilizes regularly updated site data to generate predictions of quantity variances from the plan and enable a more accurate forecast of future progress based on historical data on concrete activities. Also, the outputs of this model can be used when creating a schedule for a new project. New schedules created with the help of this model will be more consistent and reliable due to its vast data pool and ability to generate realistic forecasts from this data. The model utilizes data from completed and other ongoing projects to generate insights and provide a more accurate and efficient construction planning and scheduling solution. Within the scope of this study, different attributes of concrete pouring activities of different projects and locations were used as input data for a machine learning process, and then, using this model on test data, the forecast concrete quantities were obtained. This model provides a more advanced solution than traditional project management tools by incorporating machine learning techniques while significantly improving construction planning, scheduling accuracy, and efficiency, leading to more successful projects and increased profitability for construction companies

Published
2023
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