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Due to the ability to handle specific characteristics of economics and finance forecasting problems like e.g. non-linear relationships, behavioral changes, or knowledge-based domain segmentation, we have recently witnessed a phenomenal growth of the application of computational intelligence methodologies in this field. In this volume, Chen and Wang collected not just works on traditional computational intelligence approaches like fuzzy logic, neural networks, and genetic algorithms, but also examples for more recent technologies like e.g. rough sets, support vector machines, wavelets, or ant algorithms. After an introductory chapter with a structural description of all the methodologies, the subsequent parts describe novel applications of these to typical economics and finance problems like business forecasting, currency crisis discrimination, foreign exchange markets, or stock markets behavior.
Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.
The integration of AI-powered e-gamified modules in education has significantly impacted students' scientific attitudes and academic achievement in science. This study investigates how AI-driven gamification enhances engagement, critical thinking, and problem-solving skills, leading to improved academic performance. AI enables personalized learning experiences by adapting to individual student needs, thus fostering a more interactive and learner-centered approach. E-gamified modules provide immediate feedback, motivating students to correct errors and reinforce learning. The main aim of the study is to find out whether there is any significant difference between pre-test & post-test mean sco...
This volume includes selected contributions presented during the 3rd edition of the international conference on WaterEnergyNEXUS, which was held in Tunisia in December 2020. This conference was organized by the University of Sfax (Tunisia), in cooperation with the Sanitary Environmental Engineering Division (SEED) of the University of Salerno (Italy), the Advanced Institute of Water Industry at Kyungpook National University (Korea) and The Energy and Resources Institute, TERI (India). The WaterEnergyNEXUS series of conferences are supported by the UNESCO World Water Association Programme (WWAP) and the International Water Association (IWA). It also enjoys the patronage of several internation...
"Geospatial Information" is spatial data concerning a place or, in space, collected in real time. Geospatial techniques together with remote sensing, geographic information science, Global Positioning System (GPS), cartography, geovisualization, and spatial statistics are being used to capture, store, manipulate and analyze to understand complex situations to solve mysteries of the universe. These techniques have been applied in various fields such as meteorology, forestry, environmental management, agriculture, health, homeland security etc. around the globe. This volume presents case studies and examples from various parts of the world and provides a broad overview of various approaches; d...
Intelligent Environments (IEs) aim to empower users by enriching their experience, raising their awareness and enhancing their management of their surroundings. The term IE is used to describe the physical spaces where ICT and pervasive technologies are used to achieve specific objectives for the user and/or the environment. The growing IE community, from academia to practitioners, is working on the materialization of IEs driven by the latest technological developments and innovative ideas. This book presents the proceedings of the workshops held in conjunction with the 15th International Conference on Intelligent Environments (IE’19), Rabat, Morocco, 24 – 27 June 2019. The conference fo...
The term Intelligent Environments (IEs) refers to the physical spaces in which IT and other pervasive computing technologies are integrated and used to achieve specific goals for the user, the environment or both. The ultimate objectives of IEs are enriching user experience, enabling better management and increasing user awareness of that environment. This book presents the proceedings of the 13th International Conference on Intelligent Environments, held in Seoul, Korea, in August 2017. The conference provides a multidisciplinary collaborative forum for researchers and practitioners from computer science, electronic engineering, building architecture, art and design, sociology, government a...
Precision farming is an agricultural management system using global navigation satellite systems, geographic information systems, remote sensing, and data management systems for optimizing the use of nutrients, water, seed, pesticides and energy in heterogeneous field situations. This book provides extensive information on the state-of-the-art of research on precision crop protection and recent developments in site-specific application technologies for the management of weeds, arthropod pests, pathogens and nematodes. It gives the reader an up-to-date and in-depth review of both basic and applied research developments. The chapters discuss I) biology and epidemiology of pests, II) new sensor technologies, III) applications of multi-scale sensor systems, IV) sensor detection of pests in growing crops, V) spatial and non-spatial data management, VI) impact of pest heterogeneity and VII) precise mechanical and chemical pest control.
This book is essential for anyone interested in understanding how smart agriculture, utilizing information and technology such as computer vision and deep learning, can revolutionize agriculture productivity, resolve ongoing concerns, and enhance economic and general effectiveness in farming. The need for a reliable food supply has driven the development of smart agriculture, which leverages technology to assist farmers, especially in remote areas. A key component is computer vision (CV) technology, which, combined with deep learning, can manage agricultural productivity and enhance automation systems for improved efficiency and cost-effectiveness. Automation in agriculture ensures benefits like reduced costs, high performance, and accuracy. Aerial imaging and high-throughput research enable effective crop monitoring and management. Computer vision and AI models aid in detecting plant health, impurities, and pests, supporting sustainable farming. This book explores using CV and AI to develop smart agriculture through deep learning, data mining, and intelligent applications.