In recent years,with the prosperity of world trade,the water transport industry has developed rapidly,the number of ships has surged,and ship safety accidents in busy waters and complex waterways have become more freq...In recent years,with the prosperity of world trade,the water transport industry has developed rapidly,the number of ships has surged,and ship safety accidents in busy waters and complex waterways have become more frequent.Predicting the movement of the ship and analyzing the trajectory of the ship are of great significance for improving the safety level of the ship.Aiming at the multi-dimensional characteristics of ship navigation behavior and the accuracy and real-time requirements of ship traffic service system for ship trajectory prediction,a ship navigation trajectory prediction method combining ship automatic identification system information and Back Propagation(BP)neural network are proposed.According to the basic principle of BP neural network structure,the BP neural network is trained by taking the characteristic values of ship navigation behavior at three consecutive moments as input and the characteristic values of ship navigation behavior at the fourth moment as output to predict the future ship navigation trajectory.Based on the Automatic Identification System(AIS)information of the waters near the Nanpu Bridge in Pudong New Area,Shanghai,the results show that the method is used to predict the ship's navigational behavior eigenvalues accurately and in real time.Compared with the traditional kinematics prediction trajectory method,the model can effectively predict ship navigation.The trajectory improves the accuracy of the ship's motion situation prediction,and has the advantages of high computational efficiency and strong versatility,and the error is within an acceptable range.展开更多
An adaptive support vector machine decision feedback equalizer（ASVM-DFE） based on the least square support vector machine（LS-SVM） is proposed,it solves linear system iteratively with less computational intensity.A...An adaptive support vector machine decision feedback equalizer（ASVM-DFE） based on the least square support vector machine（LS-SVM） is proposed,it solves linear system iteratively with less computational intensity.An adaptive non-singleton fuzzy support vector machine decision feedback equalizer（ANSFSVMDFE） is also presented,it adopts the non-singleton fuzzy Gaussian kernel function with similar characteristic of pre-filter and is modified with a space transformation based approach.Simulations under nonlinear time variant channels show that ASVM-DFE and ANSFSVM-DFE perform very well on nonlinear equalization and ANSFSVM-DFE acts especially well in resisting abrupt interference.展开更多
Pig body measurement is an important evaluation criterion for breeding and production management.Automatic measurement algorithms for pig body sizes exhibit sensitivity to the point cloud posture,but non-standard pig ...Pig body measurement is an important evaluation criterion for breeding and production management.Automatic measurement algorithms for pig body sizes exhibit sensitivity to the point cloud posture,but non-standard pig postures may result in inaccurate joint point localization in body measurement,further affecting measurement accuracy and the commercial application of these algorithms.To address this challenge,this paper proposed a pig point cloud posture transformation method based on pig’s skeleton model to adjust non-standard postures before conducting body size measurements.The method utilized an improved L1-median skeleton model to extract the three-dimensional skeleton of the pig point cloud,capturing the skeleton joint points on the target pig’s head,body,and limbs.By binding the skeleton joint points with the local point cloud and using rotation matrices,non-standard postures were adjusted to standard ones,enabling accurate body size measurements.The experimental results demonstrated that the average relative errors between the transferred posture and the original standard posture were reduced to 0.89%in body length,0.76%in body width(front),1%in body width(back),0.89%in body height(front),1.7%in body height(back),2.03%in thoracic circumference,3.37%in abdominal circumference,and 1.89%in rump circumference.To conclude,the posture standardization transfer method can significantly reduce errors in important body size parameters such as body length,body height,and body width.The method displays a greater stability and robustness compared to existing posture normalization and regression adjustment methods,providing both guidance and insight for future research in intelligent agriculture.展开更多
文摘In recent years,with the prosperity of world trade,the water transport industry has developed rapidly,the number of ships has surged,and ship safety accidents in busy waters and complex waterways have become more frequent.Predicting the movement of the ship and analyzing the trajectory of the ship are of great significance for improving the safety level of the ship.Aiming at the multi-dimensional characteristics of ship navigation behavior and the accuracy and real-time requirements of ship traffic service system for ship trajectory prediction,a ship navigation trajectory prediction method combining ship automatic identification system information and Back Propagation(BP)neural network are proposed.According to the basic principle of BP neural network structure,the BP neural network is trained by taking the characteristic values of ship navigation behavior at three consecutive moments as input and the characteristic values of ship navigation behavior at the fourth moment as output to predict the future ship navigation trajectory.Based on the Automatic Identification System(AIS)information of the waters near the Nanpu Bridge in Pudong New Area,Shanghai,the results show that the method is used to predict the ship's navigational behavior eigenvalues accurately and in real time.Compared with the traditional kinematics prediction trajectory method,the model can effectively predict ship navigation.The trajectory improves the accuracy of the ship's motion situation prediction,and has the advantages of high computational efficiency and strong versatility,and the error is within an acceptable range.
文摘An adaptive support vector machine decision feedback equalizer（ASVM-DFE） based on the least square support vector machine（LS-SVM） is proposed,it solves linear system iteratively with less computational intensity.An adaptive non-singleton fuzzy support vector machine decision feedback equalizer（ANSFSVMDFE） is also presented,it adopts the non-singleton fuzzy Gaussian kernel function with similar characteristic of pre-filter and is modified with a space transformation based approach.Simulations under nonlinear time variant channels show that ASVM-DFE and ANSFSVM-DFE perform very well on nonlinear equalization and ANSFSVM-DFE acts especially well in resisting abrupt interference.
基金supported by the National Key R&D Program(2023YFD1300202)National Natural Science Foundation of China(Grant No.32172780)Key Laboratory of Smart Agricultural Technology in Tropical South China,National Engineering Research Center for Breeding Swine Industry,and Guangdong Engineering Technology Research Center for Agricultural Farming Internet of Things.
文摘Pig body measurement is an important evaluation criterion for breeding and production management.Automatic measurement algorithms for pig body sizes exhibit sensitivity to the point cloud posture,but non-standard pig postures may result in inaccurate joint point localization in body measurement,further affecting measurement accuracy and the commercial application of these algorithms.To address this challenge,this paper proposed a pig point cloud posture transformation method based on pig’s skeleton model to adjust non-standard postures before conducting body size measurements.The method utilized an improved L1-median skeleton model to extract the three-dimensional skeleton of the pig point cloud,capturing the skeleton joint points on the target pig’s head,body,and limbs.By binding the skeleton joint points with the local point cloud and using rotation matrices,non-standard postures were adjusted to standard ones,enabling accurate body size measurements.The experimental results demonstrated that the average relative errors between the transferred posture and the original standard posture were reduced to 0.89%in body length,0.76%in body width(front),1%in body width(back),0.89%in body height(front),1.7%in body height(back),2.03%in thoracic circumference,3.37%in abdominal circumference,and 1.89%in rump circumference.To conclude,the posture standardization transfer method can significantly reduce errors in important body size parameters such as body length,body height,and body width.The method displays a greater stability and robustness compared to existing posture normalization and regression adjustment methods,providing both guidance and insight for future research in intelligent agriculture.
