tiwari prayag (37 resultados)

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Taschenbuch. Condición: Neu. Neuware -Master's Thesis from the year 2017 in the subject Computer Sciences - Industry 4.0, grade: 5.0/5.0, , course: Computer Science and Engineering, language: English, abstract: Accident data analysis is one of the prime interests in the present era. Analysis of accident is very essential because it can expose the relationship between the different types of attributes that commit to an accident. Road, traffic and airplane accident data have different nature in comparison to other real world data as accidents are uncertain. Analyzing diverse accident dataset can provide the information about the contribution of these attributes which can be utilized to deteriorate the accident rate. Nowadays, Data mining is a popular technique for examining the accident dataset. In this study, Association rule mining, different classification, and clustering techniques have been implemented on the dataset of the road, traffic accidents, and an airplane crash. Achieved result illustrated accuracy at a better level and found many different hidden circumstances that would be helpful to deteriorate accident ratio in near future.Books on Demand GmbH, Überseering 33, 22297 Hamburg 84 pp. Englisch.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Master's Thesis from the year 2017 in the subject Computer Sciences - Industry 4.0, grade: 5.0/5.0, , course: Computer Science and Engineering, language: English, abstract: Accident data analysis is one of the prime interests in the present era. Analysis of accident is very essential because it can expose the relationship between the different types of attributes that commit to an accident. Road, traffic and airplane accident data have different nature in comparison to other real world data as accidents are uncertain. Analyzing diverse accident dataset can provide the information about the contribution of these attributes which can be utilized to deteriorate the accident rate. Nowadays, Data mining is a popular technique for examining the accident dataset. In this study, Association rule mining, different classification, and clustering techniques have been implemented on the dataset of the road, traffic accidents, and an airplane crash. Achieved result illustrated accuracy at a better level and found many different hidden circumstances that would be helpful to deteriorate accident ratio in near future.

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Paperback. Condición: new. Paperback. The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis.Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision makingShowcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systemsPresents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysisThis reference text addresses different applications of computational neuro-sciences using articial intelligence, deep learning, and other machine learning techniques to ne-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the elds of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering. The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Master's Thesis from the year 2017 in the subject Computer Sciences - Industry 4.0, grade: 5.0/5.0, , course: Computer Science and Engineering, language: English, abstract: Accident data analysis is one of the prime interests in the present era. Analysis of accident is very essential because it can expose the relationship between the different types of attributes that commit to an accident. Road, traffic and airplane accident data have different nature in comparison to other real world data as accidents are uncertain. Analyzing diverse accident dataset can provide the information about the contribution of these attributes which can be utilized to deteriorate the accident rate. Nowadays, Data mining is a popular technique for examining the accident dataset. In this study, Association rule mining, different classification, and clustering techniques have been implemented on the dataset of the road, traffic accidents, and an airplane crash. Achieved result illustrated accuracy at a better level and found many different hidden circumstances that would be helpful to deteriorate accident ratio in near future. 84 pp. Englisch.

Paperback. Condición: new. Paperback. The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis.Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision makingShowcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systemsPresents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysisThis reference text addresses different applications of computational neuro-sciences using articial intelligence, deep learning, and other machine learning techniques to ne-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the elds of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering. The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Kamal Malik is currently working as a Professor in CSE in the School of Engineering and Technology at CTU Ludhiana, Punjab, India. She has published Scientific Research Publications in reputed International Journals, including SCI and Scopus i.

Paperback. Condición: new. Paperback. The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis.Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision makingShowcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systemsPresents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysisThis reference text addresses different applications of computational neuro-sciences using articial intelligence, deep learning, and other machine learning techniques to ne-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the elds of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering. The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.