auerbach publications aug 2024 (2 risultati)

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is a collection of essays from key researchers in the field of project management who describe what they feel are the most impactful findings from research. In the challenging and competitive world of project management, project managers need all the insight they can get. Leading researchers share what they believe are the most important findings from the research being done today. These cover pressing topics confronting project managers, including hybrid methodologies, schedule overruns, schedule estimation, project efficiency, and managing local stakeholders. Highlights include the following:Jeff Pinto and Kate Davis explore the 'Normalization of Deviance' (NoD) phenomenon within various organizational settings, focusing on projects. NoD involves the gradual acceptance of deviant practices, diverging from established norms, and often leading to detrimental outcomes.Francesco Di Maddaloni investigates how local communities' stakeholders are perceived, identified, and categorized by project managers in major public infrastructure and construction projects (MPIC). His chapter helps project managers to have a better understanding of a more inclusive and holistic approach to engage with a broader range of stakeholders.Lavagnon Ika, Peter Love, and Jeff Pinto suggest that error and bias combine to exact a toll on major projects, offer theoretical insights, and outline practical recommendations for project managers.Jonas Söderlund offers managerial guidelines for leveraging deadlines as powerful tools for generating project success.Pedro M. Serrador looks at empirical studies that link planning quality to project success, emphasizing its importance. He also discusses the downsides of excessive planning, particularly in dynamic environments and research and development projects. 192 pp. Englisch.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the machine learning paradigm in diversified fields of technology. Deep Learning Concepts in Operations Research looks at the concepts that are the foundation of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomena. Such fields as object classification, speech recognition, and face detection have sought extensive application of artificial intelligence (AI) and ML as well. Among a variety of topics, the book examines:An overview of applications and computing devicesDeep learning impacts in the field of AIDeep learning as state-of-the-art approach to AIExploring deep learning architecture for cutting-edge AI solutionsOperations research is the branch of mathematics for performing many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects for decision making. Discussing how a proper decision depends on several factors, the book examines how AI and ML can be used to model equations and define constraints to solve problems and discover proper and valid solutions more easily. It also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost. 278 pp. Englisch.