Muddassar Farooq

TL;DR: A bee-inspired power aware routing protocol, BeeSensor, that utilizes a simple bee agent model and requires little processing and network resources is proposed, demonstrating better performance in a dynamic WSNs scenario as compared to a WSN optimized version of Adhoc On-demand Distance Vector protocol.

TL;DR: This chapter discusses the properties and review the main instances of network routing algorithms whose bottom-up design has been inspired by collective behaviors of social insects such as ants and bees, and points out their distinctive features.

TL;DR: This book introduces a multipath routing algorithm for packet-switched telecommunication networks based on techniques observed in bee colonies that is dynamic, simple, efficient, robust and flexible, and represents an important step towards intelligent networks that optimally manage resources.

TL;DR: A comprehensive survey of existing state-of-the-art Nature inspired routing protocols for fixed telecommunication networks developed by researchers who are trained in novel and different design doctrines and practices is provided.

TL;DR: In this article, a comprehensive evaluation of a set of diverse machine learning schemes on a number of biomedical datasets is presented, where the authors follow a four step evaluation methodology: (1) preprocessing the datasets to remove any redundancy, (2) classification of the datasets using six different machine learning algorithms; Naive Bayes (probabilistic), multi-layer perceptron (neural network), SMO (support vector machine), IBk (instance based learner), J48 (decision tree) and RIPPER (rule-based induction), and combining the best