scholarly journals HAZOP Ontology Semantic Similarity Algorithm Based on ACO-GRNN

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2115
Author(s):  
Yujie Bai ◽  
Dong Gao ◽  
Lanfei Peng
Keyword(s):  
Semantic Similarity ◽  
Petrochemical Industry ◽  
Expert Knowledge ◽  
Safety Evaluation ◽  
Semantic Distance ◽  
Propagation Path ◽  
Analysis Method ◽  
Pearson Coefficient ◽  
Knowledge Expression ◽  
Similarity Algorithm

Hazard and operability (HAZOP) is an important safety analysis method, which is widely used in the safety evaluation of petrochemical industry. The HAZOP analysis report contains a large amount of expert knowledge and experience. In order to realize the effective expression and reuse of knowledge, the knowledge ontology is constructed to store the risk propagation path and realize the standardization of knowledge expression. On this basis, a comprehensive algorithm of ontology semantic similarity based on the ant clony optimization generalized neural network (ACO-GRNN) model is proposed to improve the accuracy of semantic comparison. This method combines the concept name, semantic distance, and improved attribute coincidence calculation method, and ACO-GRNN is used to train the weights of each part, avoiding the influence of manual weighting. The results show that the Pearson coefficient of this method reaches 0.9819, which is 45.83% higher than the traditional method. It could solve the problems of semantic comparison and matching, and lays a good foundation for subsequent knowledge retrieval and reuse.

scholarly journals An improved semantic similarity algorithm based on HowNet and CiLin

2020 ◽  
Vol 309 ◽  
pp. 03004
Author(s):  
Ying Wang ◽  
Xiwei Feng ◽  
Yue Zhang ◽  
Haiming Chen ◽  
Lijie Xing
Keyword(s):  
Semantic Similarity ◽  
Calculation Method ◽  
Improved Method ◽  
Data Set ◽  
Specific Calculation ◽  
Word Similarity ◽  
Pearson Coefficient ◽  
Similarity Calculation ◽  
Similarity Algorithm

This paper explores an improved method for the semantic similarity calculation of words combined with HowNet and CiLin. Firstly, we designing the algorithm based on HowNet’s sememe similarity improvement calculation, comprehensively considering the influence of each part of sememe on the overall meaning, and improving the calculation of word similarity based on HowNet by changing the specific calculation method of each part of sememe. At the same time, we adopt different strategies for the different results obtained in the similarity calculation of CiLin. The experimental RG data set proves that the modified Pearson coefficient of the method reaches 0.87.

scholarly journals Statistical and Criticality Analysis of the Lower Ionosphere Prior to the 30 October 2020 Samos (Greece) Earthquake (M6.9), Based on VLF Electromagnetic Propagation Data as Recorded by a New VLF/LF Receiver Installed in Athens (Greece)

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 676
Author(s):  
Dimitrios Z. Politis ◽  
Stelios M. Potirakis ◽  
Yiannis F. Contoyiannis ◽  
Sagardweep Biswas ◽  
Sudipta Sasmal ◽  
...  
Keyword(s):  
Time Series ◽  
Fresnel Zone ◽  
Lower Ionosphere ◽  
Propagation Path ◽  
Northern Coast ◽  
Analysis Method ◽  
Ionospheric Propagation ◽  
Amplitude Data ◽  
Natural Time ◽  
Criticality Analysis

In this work we present the statistical and criticality analysis of the very low frequency (VLF) sub-ionospheric propagation data recorded by a VLF/LF radio receiver which has recently been established at the University of West Attica in Athens (Greece). We investigate a very recent, strong (M6.9), and shallow earthquake (EQ) that occurred on 30 October 2020, very close to the northern coast of the island of Samos (Greece). We focus on the reception data from two VLF transmitters, located in Turkey and Israel, on the basis that the EQ’s epicenter was located within or very close to the 5th Fresnel zone, respectively, of the corresponding sub-ionospheric propagation path. Firstly, we employed in our study the conventional analyses known as the nighttime fluctuation method (NFM) and the terminator time method (TTM), aiming to reveal any statistical anomalies prior to the EQ’s occurrence. These analyses revealed statistical anomalies in the studied sub-ionospheric propagation paths within ~2 weeks and a few days before the EQ’s occurrence. Secondly, we performed criticality analysis using two well-established complex systems’ time series analysis methods—the natural time (NT) analysis method, and the method of critical fluctuations (MCF). The NT analysis method was applied to the VLF propagation quantities of the NFM, revealing criticality indications over a period of ~2 weeks prior to the Samos EQ, whereas MCF was applied to the raw receiver amplitude data, uncovering the time excerpts of the analyzed time series that present criticality which were closest before the Samos EQ. Interestingly, power-law indications were also found shortly after the EQ’s occurrence. However, it is shown that these do not correspond to criticality related to EQ preparation processes. Finally, it is noted that no other complex space-sourced or geophysical phenomenon that could disturb the lower ionosphere did occur during the studied time period or close after, corroborating the view that our results prior to the Samos EQ are likely related to this mainshock.

scholarly journals Event Detection through Lexical Chain Based Semantic Similarity Algorithm

2021 ◽  
Vol 1166 (1) ◽  
pp. 012016
Author(s):  
Swati Jain ◽  
Suraj Prakash Narayan ◽  
Nalini Meena ◽  
Rupesh Kumar Dewang ◽  
Utkarsh Bhartiya ◽  
...  
Keyword(s):  
Semantic Similarity ◽  
Event Detection ◽  
Similarity Algorithm ◽  
Lexical Chain

scholarly journals Towards a Framework of Operational-Risk Assessment for a Maritime Autonomous Surface Ship

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3879
Author(s):  
Cunlong Fan ◽  
Jakub Montewka ◽  
Di Zhang
Keyword(s):  
Expert Knowledge ◽  
Safety Evaluation ◽  
Manual Control ◽  
Operational Mode ◽  
Surface Ship ◽  
Open Questions ◽  
Study Results ◽  
Operational Modes ◽  
Mass Case

Global research interest in the domain of maritime autonomous surface ships (MASS) is dramatically increasing. With new prototypes planned to be set to the seas where various operational modes (OMs) are claimed, the issue of the safety evaluation of an MASS, and criteria for selecting the appropriate OM for given conditions remain open questions. This paper proposes a four-step risk-informed framework to assess risk in a scenario for an MASS operating at one of three OMs: manual control (MC), remote control (RC), and autonomous control (AC). To this end, the concept of risk priority numbers (RPNs), adopted from failure mode and effects analysis (FMEA), is utilized. The required parameters to defined RPNs are obtained in the course of analyzing a model MASS accident with expert knowledge. The applicability of the proposed framework is demonstrated via a model MASS case study. Results reveal that, in the same scenario, the risk of MASS varied across the analyzed OMs. On the basis of the aggregated results for each operational mode, suggestions for OM switching are put forward.

scholarly journals An weighted ontology-based semantic similarity algorithm for web service

2009 ◽  
Vol 36 (10) ◽  
pp. 12480-12490 ◽  
Author(s):  
Min Liu ◽  
Weiming Shen ◽  
Qi Hao ◽  
Junwei Yan
Keyword(s):  
Web Service ◽  
Semantic Similarity ◽  
Similarity Algorithm

An Analysis Method of Semantic Relevancy on Controlled Tag

2012 ◽  
Vol 263-266 ◽  
pp. 1588-1592
Author(s):  
Jiu Qing Li ◽  
Chi Zhang ◽  
Peng Zhou Zhang
Keyword(s):  
Semantic Similarity ◽  
Calculation Method ◽  
Domain Ontology ◽  
Analysis Method ◽  
Semantic Correlation ◽  
Retrieval Efficiency ◽  
Similarity Calculation

To solve resource-tagging inefficiency and low-precision retrieval in special field, an analysis method of tag semantic relevancy based on controlled database was proposed. The characteristic of special field and building method for controlled database were discussed. Domain ontology correlation calculation method was used to get semantic correlation. The tag semantic similarity calculation method was developed for semantic similarity, and normalization was used to increase the similarity accuracy. With semantic correlation and similarity as parameters, the semantic relevancy in special field can be obtained. This method was used successfully in the special field of actual projects, improved resource-tagging and retrieval efficiency.

Research on the Subjective Topic Grading Agorithm Based on the Computer Course

2014 ◽  
Vol 1049-1050 ◽  
pp. 1514-1517
Author(s):  
Sai Dong Lv ◽  
Ji Li Xie
Keyword(s):  
Semantic Similarity ◽  
Calculation Method ◽  
Original Method ◽  
Sentence Similarity ◽  
Similarity Calculation ◽  
Similarity Algorithm ◽  
Computer Course ◽  
Calculation Results ◽  
Multi Level ◽  
Level Fusion

Subjective question marking system at present is affected by the attention of people, the subjective topic grading principles are common contrast degree of exam questions similar to those of the reference answer, and based on the improved semantic similarity algorithm, calculation of sentence similarity, the similarity degree of exam questions and reference answer is obtained, thus give scores.And design based on semantic similarity experiment, the experiment results show that the proposed multi-level fusion similarity calculation method to improve the original method, on the basis of integration advantages of various methods, make the calculation results meet the requirements of the scoring system.

A GRAPH-BASED SEMANTIC SIMILARITY MEASURE FOR THE GENE ONTOLOGY

2011 ◽  
Vol 09 (06) ◽  
pp. 681-695 ◽  
Author(s):  
MARCO A. ALVAREZ ◽  
CHANGHUI YAN
Keyword(s):  
Gene Ontology ◽  
Semantic Similarity ◽  
Common Ancestor ◽  
State Of The Art ◽  
Sequence Similarity ◽  
Similarity Score ◽  
Gene Products ◽  
Semantic Similarity Measure ◽  
Similarity Algorithm ◽  
Go Terms

Existing methods for calculating semantic similarities between pairs of Gene Ontology (GO) terms and gene products often rely on external databases like Gene Ontology Annotation (GOA) that annotate gene products using the GO terms. This dependency leads to some limitations in real applications. Here, we present a semantic similarity algorithm (SSA), that relies exclusively on the GO. When calculating the semantic similarity between a pair of input GO terms, SSA takes into account the shortest path between them, the depth of their nearest common ancestor, and a novel similarity score calculated between the definitions of the involved GO terms. In our work, we use SSA to calculate semantic similarities between pairs of proteins by combining pairwise semantic similarities between the GO terms that annotate the involved proteins. The reliability of SSA was evaluated by comparing the resulting semantic similarities between proteins with the functional similarities between proteins derived from expert annotations or sequence similarity. Comparisons with existing state-of-the-art methods showed that SSA is highly competitive with the other methods. SSA provides a reliable measure for semantics similarity independent of external databases of functional-annotation observations.

Semantic Retrieval for Ontology-Based Aircraft Fault Knowledge

2014 ◽  
Vol 945-949 ◽  
pp. 3410-3417
Author(s):  
Yang Zhou ◽  
Bin Tian ◽  
Zhao Yang Zeng ◽  
Zhi Yu Jia ◽  
Yan Zhou
Keyword(s):  
Semantic Distance ◽  
Semantic Retrieval ◽  
Retrieval Model ◽  
Retrieval Method ◽  
Conceptual Similarity ◽  
Aviation Maintenance ◽  
Distance Calculation ◽  
Ontology Model ◽  
Similarity Algorithm ◽  
Density Factor

With consideration of the actual requirement of fault knowledge retrieval in current aviation maintenance, semantic retrieval method for ontology-based aircraft fault knowledge is studied. Based on the concepts of semantic and semantic retrieval, it is proposed that the knowledge representation of ontology is applicable for semantic retrieval. On the basis of aircraft fault ontology model, the semantic retrieval model has been established, and the concept-matching similarity algorithm using semantic distance of ontology concepts is proposed. In the semantic retrieval method, the depth factor and density factor of ontology model are expressed, and the semantic distance calculation and the transformation function from semantic distance to conceptual similarity are proposed. The semantic retrieval research provides support for efficient application of ontology-based aircraft fault knowledge.

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