Optimized wavelet-based satellite image de-noising with multi-population differential evolution-assisted Harris Hawks Optimization Algorithm

In this research, we propose to utilize the newly introduced Multi-population differential evolution-assisted Harris Hawks Optimization Algorithm (CMDHHO) in the optimization process for satellite image denoising in the wavelet domain. This optimization algorithm is the improved version of the previous HHO algorithm which consists of chaos, multi-population, and differential evolution strategies. In this study, we applied several optimization algorithms in the optimization procedure and we compared the de-noising results with CMDHHO based noise suppression as well as with the Thresholding Neural Network (TNN) approaches. It is observed that applying the CMDHHO algorithm provides us with better qualitative and quantitative results comparing with other optimized and TNN based noise removal techniques. In addition to the quality and quantity improvement, this method is computationally efficient and improves the processing time. Based on the experimental analysis, optimized based noise suppression performs better than TNN based image de-noising. Peak Signal to Noise Ratio (PSNR) and Mean Structural Similarity Index (MSSIM) are used to evaluate and measure the performance of different de-noising methods. Experimental results indicate the superiority of the proposed CMDHHO based satellite image de-noising over other available approaches in the literature

Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management

The main aim of this book is to present various implementations of ML methods and metaheuristic algorithms to improve modelling and prediction hydrological and water resources phenomena having vital importance in water resource management

Urban Street Networks and Sustainable Transportation

Urban street space is challenged with a variety of emerging usages and users, such as various vehicles with different speeds, passenger pick-up and drop-off by mobility services, increasing parking demand for a variety of private and shared vehicles, new powertrains (e.g., charging units), and new vehicles and services fueled by digitalization and vehicle automation. These new usages compete with established functions of streets such as providing space for mobility, social interactions, and cultural and recreational activities. The combination of these functions makes streets focal points of communities that do not only fulfill a functional role but also provide identity to cities. Streets are prominent parts of cities and are essential to sustainable transport plans. The main aim of the Street Networks and Sustainable Transportation collection is to focus on urban street networks and their effects on sustainable transportation. Accordingly, various street elements related to mobility, public transport, parking, design, and movement of people and goods at the street level can be included

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen