{'fraction_non_alphanumeric': 0.022573363431151242, 'fraction_numerical': 0.002257336343115124, 'mean_word_length': 5.522058823529412, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Optimal Beamforming Using Clustered Evolutionary Teaching and Learning

An improved Teaching and Learning Based Optimization algorithm, C-TLBO, is employed to obtain user-defined shaped radiation patterns. An example of 70-element linear array with a specific asymmetric mask is considered. A novel redistribution mechanism is adopted in order to increase the convergence rate of the original optimizer. The mechanism uses the concept of multiple teachers to cluster the learner groups. It triggers an extra exploration with the same exploitation of the cost function to alter the distribution of the proposed solutions. The performance is validated using a set of standard objective functions. Comparisons to Gradient Descent (GD), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) illustrate a superior performance for designing such large dimensional beam-shaping problem.