The Transformation of Organizational Decision Making through Intelligent Decision Support, Artificial Intelligence and Big Data are now pervasive in companies as well as in the civil society. Their ubiquity tremendously modifies decision making processes, therefore forcing organisations to adapt willingly or unwillingly to these new contexts.A Special Issue on "The Transformation of Organisational Decision Making through Intelligent Decision Support" of the Journal of Decision Systems allows you to submit your research work in this issue!
In the last few decades, the role of numerical analysis and scientific computing has been increasing constantly, especially for the solution of real-world problems. The 2nd Volume of the Special Issue will present recent research results in numerical analysis and scientific computing: Numerical Analysis and Scientific Computing II.
Internet of Things (IoT) is a paradigm that connects multiple and diverse smart objects via the Internet. Nowadays, this paradigm is receiving a momentous interest in a number of real-life fields including industry, transport, healthcare and smart cities. Interconnected smart objects will then become the major data producers and consumers instead of humans and generate huge amounts of data using their sensors every single second. Such IoT data are inherently uncertain, erroneous and noisy on the one hand, and voluminous, distributed and continuous on the other hand.
Forests provide a wide range of products and services, but among the most urgent demands put on forest ecosystems is contributing to climate mitigation, which is why forests are given an important function for achieving climate objectives in the Paris agreement. Other initiatives, such as the EU Green Deal process, emphasize the efficient use of natural resources by moving to a circular economy and restoring biodiversity, among others.
Prepare your research for the special issue on "Big Data and Artificial Intelligence Research" in Natural Science (NS, ISSN Online: 2150-4105), which is an international academic journal devoted to the publication of original contributions in relevant areas.
Decision support systems for forest management have been steadily evolving since about 1980 in response to growing demand from forest managers for sophisticated analytical systems that can address the complexities of contemporary forest management issues such as adaptive management in the context of concerns for managing for forest ecosystem sustainability, integrity, and resilience while ensuring the provision of ecosystem services.
The severity of forest fires has increased substantially worldwide. This severity is prone to increase as a consequence of global change, e.g. climate and socioeconomic change. This suggests the need for the development of a coherent wildfire risk management strategy. This poses a challenge to forest researchers and managers as this strategy calls for methods and tools to help integrate forest and fire management planning activities that are often carried out independently of each other.
The provision of multiple functions of forests is becoming an increasingly important part of forest management. Traditional forest management is mostly timber-oriented. Forests, however, provide a broad range of ecosystem services that are critically important for society. Therefore, sustainable forest management is expected to reflect public demands with often contradictory interests which put a pressure on forests. Modern sustainable forest management has to consider more than one management objective and includes many stakeholders.
