CN-121997271-A - Ocean archaeological data fusion method based on multi-agent cooperation

Abstract

The invention discloses a marine archaeological data fusion method based on multi-agent cooperation, and belongs to the field of combination of a marine archaeological data processing technology and artificial intelligence. The method is implemented by constructing a collaborative system of a plurality of execution agents distributed and deployed in combination with a centrally deployed scheduling agent. The execution agent is responsible for acquisition, preprocessing and feature extraction of multi-source heterogeneous ocean archaeological data, and the scheduling agent is responsible for collaborative scheduling of the execution agent, fusion decision of multi-source features and feedback optimization of fusion results, so that full-flow closed-loop processing comprising dynamic parameter adjustment is formed. According to the method, the complex marine environment interference can be self-adapted through depth coordination among the intelligent agents and a feedback mechanism based on credibility evaluation, the fusion process is continuously optimized, and finally a fusion result with high credibility is output. The invention effectively improves the accuracy, the reliability and the overall system efficiency of data fusion, and provides reliable technical support for underwater site location and cultural relic identification.

Inventors

• LIU HUI
• ZHAO RUIXIANG
• CHENG WEIXING
• LIANG SHENGHONG
• ZHANG JING

Assignees

• 广州和辰信息科技有限公司

Dates

Publication Date

20260508

Application Date

20260204

Claims (4)

1. 1. A marine archaeological data fusion method based on multi-agent cooperation is characterized by being applied to a multi-source heterogeneous archaeological data fusion scene in a complex marine environment, and by constructing a cooperative processing system composed of a plurality of software agent modules, wherein the system adopts a framework of combining a plurality of execution agents distributed to be deployed with at least one dispatching agent deployed in a centralized way, the method completes collection, preprocessing and feature extraction of the marine archaeological data through the execution agents, completes cooperative dispatching of the execution agents, fusion decision of multi-source features and feedback optimization of fusion results through the dispatching agents, forms a closed loop processing flow containing dynamic parameter adjustment until a final fusion result meeting preset credibility requirements is output, and the execution agents and the dispatching agents are software modules deployed in a container mode and operate on virtualized or physical hardware nodes.
2. 2. The method of claim 1, wherein in the fusion decision process, the fusion weight is dynamically calculated by the scheduling agent responsible for the fusion decision according to the confidence score of each feature data and the current environmental interference coefficient by the following formula: Weight = base weight x feature confidence score/(1+ environmental interference coefficient); The environment interference coefficient is calculated in real time based on underwater noise intensity and water turbidity.
3. 3. The method of claim 1, wherein the feedback optimization specifically comprises comparing the preliminary fusion result with a historical archaeological database or field feedback data, and calculating the reliability by the following formula: Reliability = a x historical data match + b x field data match + y x data integrity; and if the reliability is lower than the preset threshold, sending a parameter adjustment instruction to the execution agent and the scheduling agent, and restarting the fusion process.
4. 4. The method of claim 1, wherein the system is further provided with a parameter library for storing and managing optimal collaborative parameters, environmental parameters, and fusion results in a historical fusion task, and providing initial parameter support for a new marine archaeological data fusion task.

Description

Ocean archaeological data fusion method based on multi-agent cooperation Technical Field The invention relates to the field of combination of ocean archaeological data processing technology and artificial intelligence, in particular to an ocean archaeological data fusion method based on multi-agent cooperation. Background The ocean archaeological data for ocean examination has the characteristics of multiple sources, isomerism, high noise, strong incomplete property and the like, and particularly in a dynamic ocean environment, the continuous and reliable result output is difficult to realize by the traditional data fusion method. The prior art lacks a self-adaptive fusion mechanism aiming at the dynamic change of the marine environment, and the problem of inconsistent semantics and scale among multi-source data is outstanding, so that the reliability of fusion results is low and the practicability is poor. The lack of a closed loop feedback and global optimization mechanism covering the whole flow of data acquisition, processing, fusion and evaluation makes the system unable to perform self-correction and continuous learning according to the real-time reliability of the fusion result, and limits the practicability and reliability of the system in real and complex ocean archaeological scenes. Along with development of Agent technology, a multi-Agent cooperative ocean archaeological data fusion method is needed, and the agents are introduced into a data fusion task, so that the defects of the prior art are overcome. Disclosure of Invention Aiming at the problems of large environmental interference, strong data isomerism, low reliability of fusion results and the like in marine archaeological data fusion, the invention provides a fusion method based on multi-agent cooperation, which realizes the full-flow closed-loop optimization from data acquisition to result feedback by constructing an agent framework of distributed execution and centralized scheduling. The invention designs a self-adaptive parameter adjustment mechanism aiming at the dynamic change of the ocean environment, and introduces a credibility assessment system based on historical data and field feedback, thereby realizing high-reliability and high-precision data fusion in a complex ocean archaeological scene. The technical scheme of the invention mainly comprises the following steps of expanding around a multi-agent cooperative architecture, an interaction flow and a module design, combining specific implementation details and cooperative logic of each link, and specifically comprising the following steps: Step S1, constructing a multi-role customized multi-agent collaborative architecture, and reasonably deploying five core agents, namely a data acquisition agent, a data preprocessing agent, a feature extraction agent, a fusion decision agent and a feedback optimization agent, based on the overall flow requirements of ocean archaeological data processing. Each intelligent agent has independent data processing, parameter configuration and communication capability, and preset cooperative association logic is established between the intelligent agents, so that the clear division of labor and the high efficiency of linkage are ensured. Each core intelligent agent realizes real-time information interaction and collaborative linkage through a unified communication module, and the communication module adopts a standardized interaction protocol, so that the communication requirements of different intelligent agents can be flexibly adapted, and the rapid transmission and analysis of state information, data information and instruction information among the intelligent agents are realized. The intelligent marine environment sensing system is characterized in that the intelligent marine environment sensing system can be matched and deployed with environment sensing intelligent agents, is specially used for collecting relevant parameters of marine environment, including key environment factors such as water flow speed, underwater noise intensity, water turbidity, water temperature and the like, and is used for providing data support for working parameter adjustment and cooperative linkage of each intelligent agent, assisting each intelligent agent to self-adaptively optimize a working mode according to dynamic changes of the marine environment, and reducing the influence of environmental interference on the data fusion effect. And S2, triggering each agent to start through cooperative scheduling based on a preset cooperative scheduling logic. The data acquisition agent preferentially completes access adaptation of various ocean archaeological data acquisition equipment, synchronously accesses various types of detection and introduction equipment such as sonar acoustic detection equipment, 4K underwater optical imaging equipment, geological formation detection equipment, historical literature data introduction equipment and the like, and realizes synchronous