A Weighted Graph Optimization Approach For Automatic Location Of Forest Road Networks PDF Download

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A Weighted-Graph Optimization Approach for Automatic Location of Forest Road Networks

A Weighted-Graph Optimization Approach for Automatic Location of Forest Road Networks
Author: Jürg Andreas Stückelberger
Publisher: vdf Hochschulverlag AG
Total Pages: 141
Release: 2008
Genre: Digital elevation models
ISBN: 3728132179

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In a large majority of regions where forestry activities occur, roads are the backbone of their efficient management. Automatic planning of a road network is an ongoing, challenging task. Advances have been aided by the increased availability and accuracy of digital terrain models, greater computing power, and improvements in optimization techniques. Defining the objectives and deriving adequate objective functions are crucial steps in guiding the solution toward an ideal network, especially when individual goals may conflict. For example, whereas the conservationist might prefer that a layout minimizes any detrimental impacts on the environment, the forest landowner may favor cost-minimal roads while the forest operator would like to have a dense network in order to reduce transportation costs.This thesis introduces models for three objective functions: - forest road construction and maintenance costs, - negative ecological effects from such roads, - the suitability, or attractiveness, of a network for cable-yarding.Case studies in mountainous project areas illustrate the trade-offs among these conflicting goals, and demonstrate how to optimize different objectives in order to make an optimal decision overall.


Modeling of a logistics network for wood flows from by-products and cascade utilization

Modeling of a logistics network for wood flows from by-products and cascade utilization
Author: Mohammad Sadegh Taskhiri
Publisher: Cuvillier Verlag
Total Pages: 192
Release: 2016-05-27
Genre: Business & Economics
ISBN: 3736982674

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Waste Wood and wood by-products have the potential to become attractive alternative sources of raw materials. Their efficient use is important due to the rising demand and limited supply of forest wood. Cascade utilization is gaining interest as a strategy to bridge the gap between rising wood demand and fresh wood availability. However, the economic and environmental impacts of a cascading system for wood-based products are not fully known. In this work, an investigation is conducted to determine the consequences of cascade utilization for the economic and environmental performance of logistics networks for wood flows. Two case studies in Lower Saxony consider five wood products, including medium density fiber (MDF), oriented strand board (OSB), particleboard, coated paper, and wood pellets. In the first case study, an approach for decision support is developed that consists of a mixed-integer linear programming (MILP) model. In the first case study, the MILP model is used for minimizing the costs of the logistics network for three scenarios. Then the UMBERTO software is applied to determine the quantity of CO2e of the minimized logistics network. In the second case study, the MILP model is enhanced using two objective functions, as cost and global warming potential (GWP) are considered simultaneously. In this case study, it is observed that environmental parameters such as CO2 emissions can also be implemented in the MILP. The utilization of a multi-objective optimization model brings new perspectives (the trade-off between two contradictory objective functions, for instance) in comparison to the first case study, in which CO2 is calculated as an off-line step after logistics costs are minimized. Altholz und Holz-Nebenprodukte besitzen das Potenzial, attraktive, alternative Rohstoffquellen zu werden. Ihre effiziente Nutzung ist von hoher Relevanz, da die Nachfrage nach Holz steigt und die Versorgung mit Holz aus Wäldern begrenzt ist. Um die Lücke zwischen der wachsenden Holznachfrage und - verfügbarkeit zu überbrücken, ist die Kaskadennutzung eine Strategie, welche zunehmendes Interesse erfährt. Allerdings sind die wirtschaftlichen und ökologischen Auswirkungen eines Kaskadensystems für Holzprodukte nicht vollständig bekannt. In dieser Arbeit wird eine Untersuchung durchgeführt, um die Folgen der Kaskadennutzung auf die Wirtschafts - und Umweltleistung von Logistiknetzwerken für Holzströme zu bestimmen. Im Rahmen von zwei Fallstudien in Niedersachsen werden fünf Holzprodukte, einschließlich mitteldichten Fasern (MDF), OSB-Platten (OSB), Spanplatten, beschichtetem Papier und Holz-Pellets betrachtet. In der ersten Fallstudie wird ein Ansatz zur Entscheidungsunterstützung entwickelt, der aus einem Mixed-Integer Linear Programming (MILP)-Modell besteht. Das MILP-Modell wird zuerst in drei verschiedenen Szenarien zur Minimierung der Logistikkosten angewendet. Mithilfe der UMBERTO-Software wird anschließend die Menge von CO2e bestimmt. In der zweiten Fallstudie wird das Modell für zwei Zielfunktionen weiterentwickelt und eingesetzt, bei denen die Kosten und das Treibhausgaspotenzial gleichzeitig betrachtet werden. Diese Fallstudie zeigt, dass auch Umweltparameter wie CO2-Emissionen mit MILP umgesetzt werden können. Die Verwendung eines Mehrzieloptimierungsmodells ermöglicht die Betrachtung neuer Perspektiven (zum Beispiel den Trade-off zwischen zwei widersprüchlichen Zielfunktionen) im Vergleich zur ersten Fallstudie, in welcher CO2-Emissionen in einem Offline-Schritt nach der Minimierung der Logistikkosten minimiert werden.


Explainable Artificial Intelligence for Intelligent Transportation Systems

Explainable Artificial Intelligence for Intelligent Transportation Systems
Author: Amina Adadi
Publisher: CRC Press
Total Pages: 328
Release: 2023-10-20
Genre: Technology & Engineering
ISBN: 1000968472

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Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of accuracy, the outcomes provided are not amenable to human scrutiny and can hardly be explained. This can be very problematic, especially for systems of a safety-critical nature such as transportation systems. Explainable AI (XAI) methods have been proposed to tackle this issue by producing human interpretable representations of machine learning models while maintaining performance. These methods hold the potential to increase public acceptance and trust in AI-based ITS. FEATURES: Provides the necessary background for newcomers to the field (both academics and interested practitioners) Presents a timely snapshot of explainable and interpretable models in ITS applications Discusses ethical, societal, and legal implications of adopting XAI in the context of ITS Identifies future research directions and open problems


Timber Ram

Timber Ram
Author: Daniel I. Navon
Publisher:
Total Pages: 30
Release: 1971
Genre: Forest management
ISBN:

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Popular Science

Popular Science
Author:
Publisher:
Total Pages: 128
Release: 2007-08
Genre:
ISBN:

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Popular Science gives our readers the information and tools to improve their technology and their world. The core belief that Popular Science and our readers share: The future is going to be better, and science and technology are the driving forces that will help make it better.


Ant Colony Optimization

Ant Colony Optimization
Author: Marco Dorigo
Publisher: MIT Press
Total Pages: 324
Release: 2004-06-04
Genre: Computers
ISBN: 9780262042192

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An overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.


Automated Machine Learning

Automated Machine Learning
Author: Frank Hutter
Publisher: Springer
Total Pages: 223
Release: 2019-05-17
Genre: Computers
ISBN: 3030053180

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This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.