Biological and Artificial Intelligence Environments

Biological and Artificial Intelligence Environments PDF

Author: Bruno Apolloni

Publisher: Springer Science & Business Media

Published: 2007-11-04

Total Pages: 389

ISBN-13: 1402034326

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The book reports the proceedings of the 15th Italian workshop on neural networks issued by the Italian Society on Neural Networks SIREN. The longevity recipe of this conference stands in three main points that normally renders the reading of these proceedings so interesting as appealing. 1. The topics of the neural networks is considered an attraction pole for a set of researches centered on the inherent paradigm of the neural networks, rather than on a specific tool exclusively. Thus, the subsymbolic management of the data information content constitutes the key feature of papers in various fields such as Pattern Recognition, Stochastic Optimization, Learning, Granular Computing, and so on, with a special bias toward bioinformatics operational applications. An excerpt of all these matters may be found in the book. 2. Though managed at domestic level, the conference attracts contributions from foreign researchers as well, so that in the book the reader may capture the flavor of the state of the art in the international community. 3. The conference is a meeting of friends as well. Thus the papers generally reflect a relaxed atmosphere where researchers meet to generously exchange their thought and explain their actual results in view of a common cultural growing of the community.

Artificial Neural Networks in Biological and Environmental Analysis

Artificial Neural Networks in Biological and Environmental Analysis PDF

Author: Grady Hanrahan

Publisher: CRC Press

Published: 2011-01-18

Total Pages: 206

ISBN-13: 1439812594

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Originating from models of biological neural systems, artificial neural networks (ANN) are the cornerstones of artificial intelligence research. Catalyzed by the upsurge in computational power and availability, and made widely accessible with the co-evolution of software, algorithms, and methodologies, artificial neural networks have had a profound

Artificial Intelligence Methods in the Environmental Sciences

Artificial Intelligence Methods in the Environmental Sciences PDF

Author: Sue Ellen Haupt

Publisher: Springer Science & Business Media

Published: 2008-11-28

Total Pages: 418

ISBN-13: 1402091192

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How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.

The Biological Mind

The Biological Mind PDF

Author: Alan Jasanoff

Publisher: Basic Books

Published: 2018-03-13

Total Pages: 304

ISBN-13: 154164431X

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A pioneering neuroscientist argues that we are more than our brains To many, the brain is the seat of personal identity and autonomy. But the way we talk about the brain is often rooted more in mystical conceptions of the soul than in scientific fact. This blinds us to the physical realities of mental function. We ignore bodily influences on our psychology, from chemicals in the blood to bacteria in the gut, and overlook the ways that the environment affects our behavior, via factors varying from subconscious sights and sounds to the weather. As a result, we alternately overestimate our capacity for free will or equate brains to inorganic machines like computers. But a brain is neither a soul nor an electrical network: it is a bodily organ, and it cannot be separated from its surroundings. Our selves aren't just inside our heads--they're spread throughout our bodies and beyond. Only once we come to terms with this can we grasp the true nature of our humanity.

A Biologist’s Guide to Artificial Intelligence

A Biologist’s Guide to Artificial Intelligence PDF

Author: Ambreen Hamadani

Publisher: Elsevier

Published: 2024-03-15

Total Pages: 370

ISBN-13: 0443240000

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A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms. Helps biologists succeed in understanding the concepts of Artificial Intelligence and machine learning Equips with new data mining strategies an easy interface into the world of Artificial Intelligence Enables researchers to enhance their own sphere of researching Artificial Intelligence

Artificial Intelligence and Data Science in Environmental Sensing

Artificial Intelligence and Data Science in Environmental Sensing PDF

Author: Mohsen Asadnia

Publisher: Academic Press

Published: 2022-02-09

Total Pages: 326

ISBN-13: 0323905072

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Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. Presents tools, connections and proactive solutions to take sustainability programs to the next level Offers a practical guide for making students proficient in modern electronic data analysis and graphics Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery

Creating Brain-Like Intelligence

Creating Brain-Like Intelligence PDF

Author: Bernhard Sendhoff

Publisher: Springer Science & Business Media

Published: 2009-04-02

Total Pages: 359

ISBN-13: 3642006159

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TheInternationalSymposiumCreatingBrain-LikeIntelligencewasheldinFeb- ary 2007 in Germany. The symposium brought together notable scientists from di?erent backgrounds and with di?erent expertise related to the emerging ?eld of brain-like intelligence. Our understanding of the principles behind brain-like intelligence is still limited. After all, we have had to acknowledge that after tremendous advances in areas like neural networks, computational and arti?cial intelligence (a ?eld that had just celebrated its 50 year anniversary) and fuzzy systems, we are still not able to mimic even the lower-level sensory capabilities of humans or animals. We asked what the biggest obstacles are and how we could gain ground toward a scienti?c understanding of the autonomy, ?exibility, and robustness of intelligent biological systems as they strive to survive. New principles are usually found at the interfaces between existing disciplines, and traditional boundaries between disciplines have to be broken down to see how complex systems become simple and how the puzzle can be assembled. During the symposium we could identify some recurring themes that p- vaded many of the talks and discussions. The triad of structure, dynamics and environment,theroleoftheenvironmentasanactivepartnerinshapingsystems, adaptivity on all scales (learning, development, evolution) and the amalga- tion of an internal and external world in brain-like intelligence rate high among them. Each of us is rooted in a certain community which we have to serve with the results of our research. Looking beyond our ?elds and working at the interfaces between established areas of research requires e?ort and an active process.

Artificial Intelligence Methods in the Environmental Sciences

Artificial Intelligence Methods in the Environmental Sciences PDF

Author: Sue Ellen Haupt

Publisher: Springer

Published: 2009-08-29

Total Pages: 424

ISBN-13: 9781402091285

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How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.

Using Artificial Intelligence in Chemistry and Biology

Using Artificial Intelligence in Chemistry and Biology PDF

Author: Hugh Cartwright

Publisher: CRC Press

Published: 2008-05-05

Total Pages: 358

ISBN-13: 0849384141

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Possessing great potential power for gathering and managing data in chemistry, biology, and other sciences, Artificial Intelligence (AI) methods are prompting increased exploration into the most effective areas for implementation. A comprehensive resource documenting the current state-of-the-science and future directions of the field is required to