{'fraction_non_alphanumeric': 0.03121852970795569, 'fraction_numerical': 0.0, 'mean_word_length': 5.2125, '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}}
Efficiency Scores Analysis of Coal Mines using IRS, DRS and Cross Efficiency Models

Economic growth world over is driven by energy, whether in the form of finite resources such as coal, oil and gas or in renewable forms such as hydroelectric, wind, solar and bio-mass or its converted form, electricity(power). Increased energy consumption (especially of electricity) is inevitable with higher GDP growth. Coal was created by the fossilised remains of plants and has high carbon content. DEA is a multi-factor productivity analysis model for measuring the relative efficiency of a homogenous set of coal mines (DMU’s). For every inefficient coal mine, DEA identifies a set of corresponding efficient coal mines that can be utilized as benchmarks for improvement of performance and productivity. Benchmarking and ranking of coal mines based on efficiency scores using advanced DEA models like, Increasing Returns to Scale (IRS), Decreasing Returns to Scale (DRS), Cross Efficiency (CE) Models.