{'fraction_non_alphanumeric': 0.015347334410339256, 'fraction_numerical': 0.0016155088852988692, 'mean_word_length': 4.9855072463768115, '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}}
[Effect of near infrared spectrum on the precision of PLS model for oil yield from oil shale].

It is impossible to use present measurement methods for the oil yield of oil shale to realize in-situ detection and these methods unable to meet the requirements of the oil shale resources exploration and exploitation. But in-situ oil yield analysis of oil shale can be achieved by the portable near infrared spectroscopy technique. There are different correlativities of NIR spectrum data formats and contents of sample components, and the different absorption specialities of sample components shows in different NIR spectral regions. So with the proportioning samples, the PLS modeling experiments were done by 3 formats (reflectance, absorbance and K-M function) and 4 regions of modeling spectrum, and the effect of NIR spectral format and region to the precision of PLS model for oil yield from oil shale was studied. The results show that the best data format is reflectance and the best modeling region is combination spectral range by PLS model method and proportioning samples. Therefore, the appropriate data format and the proper characteristic spectral region can increase the precision of PLS model for oil yield form oil shale.