Download or read book Artificial Neural Network Modeling of Water and Wastewater Treatment Processes written by Khataee, Ali Reza Khataee and published by Nova Science Publishers. This book was released on 2014-05-14 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Neural Network Modeling of Water and Wastewater Treatment Processes written by Ali Reza Khataee and published by Nova Novinka. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) are computer based systems that are designed to simulate the learning process of neurons in the human brain. ANNs have been attracting great interest during the last decade as predictive models and pattern recognition. Artificial neural networks possess the ability to "learn" from a set of experimental data without actual knowledge of the physical and chemical laws that govern the system. Therefore, ANNs application in data treatment is high, especially where systems present non-linearities and complex behaviour. This book describes the application of artificial neural networks for modelling of water and wastewater treatment processes.

Download or read book Artificial Intelligence Systems for Water Treatment Plant Optimization written by Christopher W. Baxter and published by American Water Works Association. This book was released on 2001 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Neural Networks in Water Supply Engineering written by Srinivasa Lingireddy and published by ASCE Publications. This book was released on 2005-01-01 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepared by the Water Supply Engineering Technical Committee of the Infrastructure Council of the Environmental and Water Resources Institute of ASCE. This report examines the application of artificial neural network (ANN) technology to water supply engineering problems. Although ANN has rarely been used in in this area, those who have done so report findings that were beyond the capability of traditional statistical and mathematical modeling tools. This report describes the availability of diverse applications, along with the basics of neural network modeling, and summarizes the experiences of groups of researchers around the world who successfully demonstrated significant benefits from using ANN technology in water supply engineering. Topics include: Forecasting salinity levels in River Murray, South Australia; Predicting gastroenteritis rates and waterborne outbreaks; Modeling pH levels in a eutrophic Middle Loire River, France; and ANNs as function approximation tools replacing rigorous mathematical simulation models for analyzing water distribution networks.

Download or read book Artificial Neural Networks written by Chi Leung Patrick Hui and published by BoD – Books on Demand. This book was released on 2011-04-11 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers 27 articles in the applications of artificial neural networks (ANN) in various disciplines which includes business, chemical technology, computing, engineering, environmental science, science and nanotechnology. They modeled the ANN with verification in different areas. They demonstrated that the ANN is very useful model and the ANN could be applied in problem solving and machine learning. This book is suitable for all professionals and scientists in understanding how ANN is applied in various areas.

Download or read book Artificial Neural Networks for Engineering Applications written by Alma Y. Alanis and published by Academic Press. This book was released on 2019-03-15 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications. Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering Contains all the theory required to use the proposed methodologies for different applications

Download or read book Research Anthology on Artificial Neural Network Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-07-16 with total page 1575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.

Download or read book Smart Energy Empowerment in Smart and Resilient Cities written by Mustapha Hatti and published by Springer Nature. This book was released on 2019-12-24 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: International Conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES2019, 26-28 November 2019, Taghit-Bechar, Algeria. The challenges of the energy transition in the medium term lead to numerous technological breakthroughs in the areas of production, optimal distribution and the rational use of energy and renewable energy (energy efficiency and optimization of consumption, massive electrification, monitoring and control energy systems, cogeneration and energy recovery processes, new and renewable energies, etc.). The fall in the cost of renewable energies and the desire for a local control of energy production are today calling for a profound change in the electricity system. Local authorities are at the center of energy developments by taking into account the local nature of certain energy systems, heat networks, geothermal energy, waste heat recovery, and electricity generation from household waste. On the other side, digital sciences are at the heart of connected objects and intelligent products that combine information processing and communication capabilities with their environment. Digital technology is at the center of new systems engineering approaches (3D modeling, virtualization, simulation, digital prototyping, etc.) for the design and development of intelligent systems. The book deals with various topics ranging from the design, development and maintenance of energy production systems, transport, distribution or storage of energy, optimization of energy efficiency, especially in the use of energy. innovation in the fields of energy production from renewable energies, management of energy networks: electricity, fluids, gas, district heating, energy storage modes: battery, super-capacitors , overseeing energy supply through supervision, control and diagnosis, risk management, as well as the design and management of smart grids: microgrid, smartgrid. This imposes the model of energy empowerment in the advent of smart cities. Empower the world’s most vulnerable energy-poor citizens and establish growing and vibrant socioeconomic communities, by academics, students in engineering and data computing from around the world who have chosen an academic path leading to an electric power and energy engineering and artificial intelligence to advancing technology for the advantage of humanity.

Download or read book Artificial Neural Networks in Hydrology written by R.S. Govindaraju and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy.

Download or read book Artificial Neural Network Modelling written by Subana Shanmuganathan and published by Springer. This book was released on 2016-02-03 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling.

Download or read book Proceedings of International Conference on Industrial Instrumentation and Control written by Subhasis Bhaumik and published by Springer. This book was released on 2023-03-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of selected high-quality research papers presented at the International Conference on Industrial Instrumentation and Control (ICI2C 2021), organized by the Department of Applied Electronics & Instrumentation Engineering, RCC Institute of Information Technology, Kolkata, India, during 20–August 22, 2021. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It covers topics such as instrumentation application in industry, instrumentation in electrical applications and instrumentation in recent trends with computation approach.

Download or read book Applications of Artificial Neural Networks in Drinking Water Treatment Process Modelling and Control written by Christopher Wayne Baxter and published by . This book was released on 2002 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Recurrent Neural Networks written by Larry Medsker and published by CRC Press. This book was released on 1999-12-20 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: With existent uses ranging from motion detection to music synthesis to financial forecasting, recurrent neural networks have generated widespread attention. The tremendous interest in these networks drives Recurrent Neural Networks: Design and Applications, a summary of the design, applications, current research, and challenges of this subfield of artificial neural networks. This overview incorporates every aspect of recurrent neural networks. It outlines the wide variety of complex learning techniques and associated research projects. Each chapter addresses architectures, from fully connected to partially connected, including recurrent multilayer feedforward. It presents problems involving trajectories, control systems, and robotics, as well as RNN use in chaotic systems. The authors also share their expert knowledge of ideas for alternate designs and advances in theoretical aspects. The dynamical behavior of recurrent neural networks is useful for solving problems in science, engineering, and business. This approach will yield huge advances in the coming years. Recurrent Neural Networks illuminates the opportunities and provides you with a broad view of the current events in this rich field.

Download or read book Dynamical Modelling Estimation in Wastewater Treatment Processes written by D. Dochain and published by IWA Publishing. This book was released on 2001-12-01 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Environmental quality is becoming an increasing concern in our society. In that context, waste and wastewater treatment, and more specifically biological wastewater treatment processes play an important role. In this book, we concentrate on the mathematical modelling of these processes. The main purpose is to provide the increasing number of professionals who are using models to design, optimise and control wastewater treatment processes with the necessary background for their activities of model building, selection and calibration. The book deals specifically with dynamic models because they allow us to describe the behaviour of treatment plants under the highly dynamic conditions that we want them to operate (e.g. Sequencing Batch Reactors) or we have to operate them (e.g. storm conditions, spills). Further extension is provided to new reactor systems for which partial differential equation descriptions are necessary to account for their distributed parameter nature (e.g. settlers, fixed bed reactors). The model building exercise is introduced as a step-wise activity that, in this book, starts from mass balancing principles. In many cases, different hypotheses and their corresponding models can be proposed for a particular process. It is therefore essential to be able to select from these candidate models in an objective manner. To this end, structure characterisation methods are introduced. Important sections of the book deal with the collection of high quality data using optimal experimental design, parameter estimation techniques for calibration and the on-line use of models in state and parameter estimators. Contents Dynamical Modelling Dynamical Mass Balance Model Building and Analysis Structure Characterisation (SC) Structural Identifiability Practical Identifiability and Optimal Experiment Design for Parameter Estimation (OED/PE) Estimation of Model Parameters Recursive State and Parameter Estimation Glossary Nomenclature

Download or read book Evaluation of Sequential Batch Reactor Wastewater Treatment Plant Using Artificial Neural Network written by Mustapha Mujeli and published by . This book was released on 2012 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Domestic wastewater is one of the main pollution sources in municipal areas. Wastewater treatment plant is obviously the most important component in eliminating the unwanted materials in domestic and industrial effluents before discharging into the water bodies. Wastewater treatment process is in use since 17th century for treating both domestic and industrial effluent, but its performance is not as expected due to lack of adequate knowledge on the mechanisms involved. The deterministic models are unable to fully comprehend the complex nature of the processes that comprises physical, chemical and biological processes of the wastewater treatment plant. The combined application of Principal Component Analysis and Artificial Neural Network tools is a recent development in modelling wastewater treatment plant characterization. Therefore, in this study artificial neural network and principal component analysis were integrated using MATLAB® to train neural network for Sequential Batch Reactor wastewater treatment plant. The study comprises optimization of the network properties; artificial neural network development and hybrid network development for influent biological oxygen demand, influent ammonical nitrogen, effluent biological oxygen demand, and effluent ammonical nitrogen of Bandar Tun Razak sewage treatment plant in Kuala Lumpur. The models were verified using separate wastewater samples collected from the plant. The results showed that hybrid model outperformed its corresponding normal artificial neural network and recorded a higher correlation coefficients for training (0.7362), testing (0.7678) and verification (0.7699) datasets with the respective mean absolute errors of 13.75, 11.29 and 12.76. The hybrid networks for the remaining model performances were lower than the normal corresponding network. The correlation coefficients (and mean absolute errors) for training, testing and verification of the best effluent biochemical oxygen demand network were 0.7990 (1.43), 0.8276 (1.76) and 0.7344 (1.73), respectively. Generally, influent and effluent ammonical nitrogen model predictions ability were weak compared to biological oxygen demand model. The best network for prediction of influent ammonical nitrogen was the normal artificial neural network model with correlation coefficients and (mean absolute errors) of 0.5648 (2.54), 0.6024 (3.48) and 0.6284 (7.63) for training, testing and verification datasets, respectively. The best model for effluent ammonical nitrogen simulation was the normal artificial neural network. It recorded the highest correlation coefficients and least (mean absolute errors) for training, testing and verification as; 0.7984 (4.18), 0.6224 (5.59) and 0.6507 (4.15), respectively. The model performances were satisfactory when compared with the published results as shown in Chapter four. The combination of principal component analysis and artificial neural network techniques to evaluate the strength of training neural networks and method of model generalization are the major contributions of this study.

Download or read book Artificial Intelligence and Modeling for Water Sustainability written by Alaa El Din Mahmoud and published by CRC Press. This book was released on 2023-04-25 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence and the use of computational methods to extract information from data are providing adequate tools to monitor and predict water pollutants and water quality issues faster and more accurately. Smart sensors and machine learning models help detect and monitor dispersion and leakage of pollutants before they reach groundwater. With contributions from experts in academia and industries, who give a unified treatment of AI methods and their applications in water science, this book help governments, industries, and homeowners not only address water pollution problems more quickly and efficiently, but also gain better insight into the implementation of more effective remedial measures. FEATURES Provides cutting-edge AI applications in water sector. Highlights the environmental models used by experts in different countries. Discusses various types of models using AI and its tools for achieving sustainable development in water and groundwater. Includes case studies and recent research directions for environmental issues in water sector. Addresses future aspects and innovation in AI field related to watersustainability. This book will appeal to scientists, researchers, and undergraduate and graduate students majoring in environmental or computer science and industry professionals in water science and engineering, environmental management, and governmental sectors. It showcases artificial intelligence applications in detecting environmental issues, with an emphasis on the mitigation and conservation of water and underground resources.

Download or read book The AI Cleanse Transforming Wastewater Treatment Through Artificial Intelligence written by Manoj Chandra Garg and published by Springer Nature. This book was released on with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: