This book addresses the prediction of the Water Quality Index (WQI) at Perak River, State of Perak, Malaysia, using a fuzzy multiple linear regression model to tackle the uncertainty in the measurements of six key parameters – dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), pH value (pH) and ammoniacal nitrogen (NH3-NL). Given its scope, the book is suitable for graduate students, researchers and water quality scientists.
This book explores key examples concerning the implementation of information technology and mathematical modeling to solve issues concerning environmental sustainability. The examples include using fuzzy weighted multivariate regression to predict the water quality index at Perak River in Malaysia; using wireless sensor networks (WSNs) for a remote river water pollution monitoring system; deriving biomass activated carbon from oil palm shell; and assessing the performance of a PV/T air solar collector. The book offers a valuable resource for all graduate students and researchers who are working in this rapidly growing area.
Since the International Institute for Applied Systems Analysis began its study of water quality modeling and management in 1977, it has been interested in the relations between uncertainty and the problems of model calibration and prediction. The work has focused on the theme of modeling poorly defined environmental systems, a principal topic of the effort devoted to environmental quality control and management. Accounting for the effects of uncertainty was also of central concern to our two case studies of lake eutrophication management, one dealing with Lake Balaton in Hungary and the other with several Austrian lake systems. Thus, in November 1979 we held a meeting at Laxenburg to discuss recent method ological developments in addressing problems associated with uncertainty and forecasting of water quality. This book is based on the proceedings of that meeting. The last few years have seen an increase in awareness of the issue of uncertainty in water quality and ecological modeling. This book is relevant not only to contemporary issues but also to those of the future. A lack of field data will not always be the dominant problem for water quality modeling and management; more sophisticated measuring techniques and more comprehensive monitoring networks will come to be more widely applied. Rather, the important problems of the future are much more likely to emerge from the enhanced facility of data processing and to concern the meaningful interpretation, assimilation., and use of the information thus obtained.
This book covers water quality indices (WQI) in depth – it describes what purpose they serve, how they are generated, what are their strengths and weaknesses, and how to make the best use of them. It is a concise and unique guide to WQIs for chemists, chemical/environmental engineers and government officials. Whereas it is easy to express the quantity of water, it is very difficult to express its quality because a large number of variables determine the water quality. WQIs seek to resolve the difficulty by translating a set of a large number of variables to a one-digit or a two-digit numeral. They are essential in communicating the status of different water resources in terms of water quality and the impact of various factors on it to policy makers, service personnel, and the lay public. Further they are exceedingly useful in the monitoring and management of water quality. With the importance of water and water quality increasing exponentially, the importance of this topic is also set to increase enormously because only with the use of indices is it possible to assess, express, communicate, and monitor the overall quality of any water source. Provides a concise guide to WQIs: their purpose and generation Compares existing methods and WQIs and outlines strengths and weaknesses Makes recommendations on how the indices should be used and under what circumstances they apply
Industry 4.0 is revolutionizing the way companies manufacture, improve, and distribute their products. It demands the application of renewable energy using advanced materials. Renewable energy is reshaping the fields of industry, agriculture, and households, providing reliable power supplies and fuel diversification. This enhances energy security, lowers the risk of fuel spills, and reduces the need for imported fuels. Examples of material applications used for renewable energy are photovoltaic, solar cells, which can be used in agriculture. This volume has a diverse audience including students, researchers, and academics engaged in materials and renewable energy. Features : Presents latest research on renewable energy in relation to urbanization, industrialization, and the environment. Provides in-depth discussion on modeling and simulation using latest techniques. Provides technical exposure for the readers on advanced materials. Provides numerous examples on properties of biomaterials and their future prospect. Provides up-to-date information on functional materials for industrial application.
This book presents peer-reviewed articles from the 1st International Conference on New Energy (ICNE 2022), held on 1–2 December at Sarawak in Malaysia. This book highlights the current trends/studies on fundamental of hydrogen technologies and the application of hydrogen as the new sustainable renewable energy. Topics included but not limited to are: hydrogen production, its storage and transportation, and hydrogen utilization. This book contributes in making green hydrogen competitive and ready for a scale up in the 2030s, towards the objective of reaching net zero emissions by 2050
This book is a collection of selected papers presented at the Third Congress on Intelligent Systems (CIS 2022), organized by CHRIST (Deemed to be University), Bangalore, India, under the technical sponsorship of the Soft Computing Research Society, India, during September 5–6, 2022. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers topics such as the Internet of Things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber-physical systems, data analytics, data/web mining, data science, intelligence for security, intelligent decision-making systems, intelligent information processing, intelligent transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video classification, soft computing for machine vision, pattern recognition, human-computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised learning, unsupervised learning, fuzzy logic, rough sets, computational optimization, and neuro-fuzzy systems.
This book provides a comprehensive yet fresh perspective for the cutting-edge CI-oriented approaches in water resources planning and management. The book takes a deep dive into topics like meta-heuristic evolutionary optimization algorithms (e.g., GA, PSA, etc.), data mining techniques (e.g., SVM, ANN, etc.), probabilistic and Bayesian-oriented frameworks, fuzzy logic, AI, deep learning, and expert systems. These approaches provide a practical approach to understand and resolve complicated and intertwined real-world problems that often imposed serious challenges to traditional deterministic precise frameworks. The topic caters to postgraduate students and senior researchers who are interested in computational intelligence approach to issues stemming from water and environmental sciences.
