PATENT CLAIM ANALYSIS

Application Number: 16313134
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-07
Patent Classification: ["705", "007250"]

Abstract:
A method for predicting fishing access of Katsuwonuspelamis purse seine fishery in the Central and Western Pacific adopts the statistical data per year before the forecast year to the previous 16 years, including year, month, longitude, latitude, fishing effort (the number of nets) and the catch (ton) in an important operation waters of 5°S-5°N, 125°E-180°E, a sea surface temperature anomaly (SSTA) in the Nino3.4 area and the sea surface temperature (SST) in the operation waters. A sea area is denoted by 5°×5° spatial resolution, the production statistical data of the sea areas are matched with the corresponding environmental data one by one to obtain the relationship between different SSTA and SST ranges of each sea area and the corresponding initial value fishing effort, a fishing access prediction model of each sea area is established by using a normal distribution model.

Claim (Index 5):
The method for predicting the fishing access of the Katsuwonuspelamis purse seine fishery in the Central and Western Pacific according to  claim 2 , wherein by adoption of the fishing access prediction model of each sea area based on the fishing access prediction model of the SSTA of NINO3.4 area and the fishing access prediction model of the SST of the operation waters obtained in the step 3, performing a prediction of the fishing access of the Katsuwonuspelamis on the sea area to obtain a predicted value of the percentage of the fishing effort of the sea area.

Metadata:
- Claim Count in Document: 11.0
- Percentile: 98.0
- Lexical Diversity: 1.89286
- Patent Class: 705.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['11887656', '10589351', '12404967', '12391972', '11740250']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.092383855859411
- 35 USC 102 Novelty (BERT): 0.4820469333534615
- Combined Prediction Score: 0.1313501636088161
- Mean Citation Score: 135.96944299999998
- Max Citation Score: 149.02068
- Similarity Product: 103.8387724421382

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test