Applied nature inspired computing: algorithms and case studies Chapter 1. Particle Swarm Optimization of Morphological Filters for Electrocardiogram Baseline Drift Estimation Chapter 2. Detection of Breast Cancer using Fusion of MLO and CC View Features Through a Hybrid Technique Based on Binary Firefly algorithm and Optimum Path Forest Classification Chapter 3. Recommending Healthy Personalized Daily Menus – A Cuckoo Search based Hyper Heuristic Approach Chapter 4. A Hybrid Bat Inspired Algorithm for Power Transmission Expansion Planning on a Practical Brazilian Network Chapter 5. An Application of Binary Grey Wolf Optimizer (BGWO) variants for Unit Commitment Problem Chapter 6. Sensorineural hearing loss identification via discrete wavelet packet entropy and cat swarm optimization Chapter 7. Chaotic Variants of Grasshopper Optimisation Algorithm and their application to Protein Structure Prediction Chapter 8. Examination of Retinal Anatomical Structures – A Study with Spider Monkey Optimization Algorithm Chapter 9. Nature Inspired Metaheuristics Search Algorithms for Solving the Economic Load Dispatch Problem of Power System: A Comparative Study Chapter 10. Parallel series System Optimization by Weighting Sum Methods and Nature inspired Computing Chapter 11. Development of Artificial Neural Networks trained by Heuristic Algorithms for Prediction of Exhaust Emissions and Performance of a Diesel Engine Fuelled with Biodiesel Blends This book presents a cutting edge research procedure in the Nature Inspired Computing (NIC) domain and its connections with computational intelligence areas in real world engineering applications. It introduces readers to a broad range of algorithms such as genetic algorithms particle swarm optimization the firefly algorithm flower pollination algorithm collision based optimization algorithm bat algorithm ant colony optimization and multi agent systems. In turn it provides an overview of meta heuristic algorithms comparing the advantages and disadvantages of each. Moreover the book provides a brief outline of the integration of nature inspired computing techniques and various computational intelligence paradigms and highlights nature inspired computing techniques in a range of applications including: evolutionary robotics sports training planning assessment of water distribution systems flood simulation and forecasting traffic control gene expression analysis antenna array design and scheduling dynamic resource management