集成电路与嵌入式系统2026，Vol.26Issue(2)：100-113,14.DOI:10.20193/j.ices2097-4191.2025.0117
基于模型集成的外塘养殖水质评估及预测系统设计
Design of water quality evaluation and prediction system for outdoor pond aquaculture based on model integration
摘要
Abstract
Outdoor pond aquaculture feeding yields significantly vary with water quality evaluation,estimation,and control.However,several issues challenge the accuracy of water evaluation,such as inexplicable missing data in acquired parameters and strong coupling and time-lag correlations among multiple parameters.Inaccurate water evaluation results further introduce errors into the estimation and control processes,potentially leading to sudden losses in aquaculture.Therefore,a real-time water parameter monitoring device is firstly designed in this research,featuring an ESP32 microcontroller and an embedded MATLAB application.This device allows real-time data on ammonia nitrogen,dissolved oxygen,pH value,water temperature,and water depth to be transmitted to the cloud platform,specif-ically the OneNet IoT platform.Based on the device design,an innovative method with VMD-LSTM-XGBoost structure for parameter decomposition and reconstruction to extraction of temporal information among parameters and the supplementation of missing data.Meanwhile,the Sparrow Search Algorithm(SSA)is employed for decomposition numbers optimization.Furthermore,the combination of AHP-CV-normal cloud model is designed to improve the accuracy of water quality evaluation.Finally,an integrated learning model is constructed to improve the accuracy of water quality prediction.This research optimized the decomposition of 4 parameter groups into 34 sets of time-series data based on collected data and completed missing parameter supplementation.The experimental validation shows that the proposed AHP-CV-normal cloud model for water quality assessment achieves a classification accuracy rate of over 98%,demon-strating good feasibility.The designed VMD-LSTM-XGBoost hybrid model achieves a test accuracy of 96.209%on the validation set,demonstrating strong predictive performance.This research provides an effective solution for monitoring water quality parameters,data imputation,water quality assessment,and prediction in the complex environment of outdoor pond aquaculture,offering theoretical sup-port for feeding strategies.关键词
外塘养殖/水质数据采集/环境参数监测评估/模型集成/环境参数预测Key words
open-pond aquaculture/water parameters acquisition/environmental parameter monitoring and evaluation/model integra-tion/environmental parameter prediction分类
信息技术与安全科学引用本文复制引用
王逸之,马丰原,丁思盈,汤盱衡,刘嘉城,季颂捷,陈林,陈维娜,肖茂华..基于模型集成的外塘养殖水质评估及预测系统设计[J].集成电路与嵌入式系统,2026,26(2):100-113,14.基金项目
江苏省农业自主科技自主创新资金项目(CX(22)3107) （CX(22）
金陵科技学院2025年学位与研究生教育教学改革课题(YJSJG25_10) （YJSJG25_10）
