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Feature Selection with Fluid Mechanics Inspired Particle Swarm Optimization for Microarray Data

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Journal of Beijing Institute of Technology 2017年第4期26卷 517-524页

作者： shengsheng wang Ruyi Dong College of Computer Science and Technology Jilin UniversityChangchun 130012China Jilin Vocational College of Industry and Technology JilinJilin 132013China

Deoxyribonucleic acid（ DNA） microarray gene expression data has been widely utilized in the field of functional genomics,since it is helpful to study cancer,cells,tissues,organisms *** the sample sizes are relatively small compared to the number of genes,so feature selection is very necessary to reduce complexity and increase the classification accuracy of samples. In this paper,a completely newimprovement over particle swarm optimization（ PSO） based on fluid mechanics is proposed for the feature selection. This newimprovement simulates the spontaneous process of the air from high pressure to lowpressure,therefore it allows for a search through all possible solution spaces and prevents particles from getting trapped in a local optimum. The experiment shows that,this newimproved algorithm had an elaborate feature simplification which achieved a very precise and significant accuracy in the classification of 8 among the 11 datasets,and it is much better in comparison with other methods for feature selection.

关键词： feature selection particle swarm optimization (PSO) fluid mechanics (FM) microarray data support vector machine (SVM)

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SPHLU:An Efficient Algorithm for Processing PRkNN Queries on Uncertain Data

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Chinese Journal of Electronics 2016年第3期25卷 403-406页

作者： wang shengsheng LI Yang CHAI Sheng BOLOU Bolou Dickson College of Computer Science and Technology Key Laboratory of Symbolic Computing and Knowledge Engineering of Ministry of EducationJilin University

Query on uncertain data has received much attention in recent years, especially with the development of Location-based services(LBS). Little research is focused on reverse k nearest neighbor queries on uncertain data. We study the Probabilistic reverse k nearest neighbor(PRkN N) queries on uncertain data. It is succinctly shown that, PRkN N query retrieves all the points that have higher probabilities than a given threshold value to be the Reverse k-nearest neighbor(RkN N) of query data *** previous works on this topic mostly process with k > *** algorithms allow the cases for k > 1, but the efficiency is inefficient especially for large k. We propose an efficient pruning algorithm — Spatial pruning heuristic with louer and upper bound(SPHLU) for solving the PRkN N queries for k > 1. The experimental results demonstrate that our algorithm is even more efficient than the existent algorithms especial for a large value of k.

关键词： Spatial database Uncertain data R-tree Probabilistic reverse k nearest neighbor queries

Improved Qualitative Trajectory Calculus for Pair-Activity Analysis

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Journal of Beijing Institute of Technology 2019年第2期28卷 318-326页

作者： shengsheng wang Guangyao wang Yungang Zhu Jingwen Shao College of Computer Science and Technology Jilin University

Trajectory provides the most robust feature for activity recognition in far-field surveillance videos,in which increasing attentions have been given to the use of qualitative methods with symbolic rather than real-value *** trajectory calculus(QTC)showed a good performance in pair-activity from ***,QTC and similar works are not good at dealing with noise,since they are all considering short-term *** deal with the problems mentioned above,two types of long-term features,including sub-trajectory feature and point-trajectory feature,are *** sub-trajectory feature is a long-term feature in a coarse granularity,while the point-trajectory feature is a long-term feature in a relatively fine *** the sub-trajectory feature,a couple of trajectories are segmented into sub-trajectories and enveloping boxes are used to substitute the original sub-trajectory for capturing the major *** point-trajectory feature describes the relationship between a single point in one trajectory and all parts of the other *** experiments on the human activity classification data demonstrated that our proposed methods are better than the original QTC and previous short-term features.

关键词： pair-activity analysis qualitative trajectory calculus sub-trajectory feature point-trajectory feature

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Interactive Activity Learning from Trajectories with Qualitative Spatio-Temporal Relation

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Chinese Journal of Electronics 2015年第3期24卷 508-512页

作者： wang shengsheng WEN Changji LAI Yong LIU Yiting LIU Dayou College of Computer Science and Technology Key Laboratory of Symbolic Computing and Knowledge Engineering of Ministry of Education Jilin University

Automatically analyzing interactions from video has gained much attention in recent years. Here a novel method has been proposed for analyzing interactions between two agents based on the tra jectories. Previous works related to this topic are methods based on features, since they only extract features from objects. A method based on qualitative spatio-temporal relations is adopted which utilizes knowledge of the model(qualitative spatio-temporal relation calculi) instead of the original tra jectory information. Based on the previous qualitative spatio-temporal relation works, such as Qualitative tra jectory calculus(QTC), some new calculi are now proposed for long term and complex interactions. By the experiments, the results showed that our proposed calculi are very useful for representing interactions and improved the interaction learning more effectively.

关键词： Interactive activity learning Tra jectory pair Qualitative spatio-temporal relation

Dual Sum-Product Networks Autoencoder for Multi-Label Classification

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Journal of Shanghai Jiaotong university(Science) 2020年第5期25卷 665-673页

作者： wang shengsheng ZHANG Hang CHEN Juan College of Computer Science and Technology Jilin UniversityChangchun 130012China College of Software Jilin UniversityChangchun 130012China

Sum-product networks(SPNs)are an expressive deep probabilistic architecture with solid theoretical foundations,which allows tractable and exact *** always act as black-box inference machine in many artificial intelligence *** to their recursive definition,SPNs can also be naturally employed as hierarchical feature ***,SPNs have been successfully employed as autoencoder framework in representation ***,SPNs autoencoder ignores the model structural duality and trains the models separately and *** this work,we propose a Dual-SPNs autoencoder which designs two SPNs autoencoders to compose as a dual *** approach trains the models simultaneously,and explicitly exploits the structural duality between them to enhance the training *** results on several multilabel classification problems demonstrate that Dual-SPNs autoencoder is very competitive against with state-of-the-art autoencoder architectures.

关键词： smn-product networks(SPNs) representation learning dual learning multi-label classification

Improved fluid search optimization-based real-time weed mapping

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Information Processing in Agriculture 2020年第3期7卷 403-417页

作者： Chengcheng Chen shengsheng wang Xianchang wang Helong Yu Ruyi Dong College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun 130012China College of Information Technology Jilin Agricultural UniversityChangchun 130118China Chengdu Kestrel Artificial Intelligence Institute Chengdu 611730China

In the field of agriculture,variable-rate herbicide spraying(VRHS)technology has been used to solve the low efficiency of pesticides and crop chemical *** key of VRHS is the quick and precise identification of weeds from field images,which forms a weed *** search optimization(FSO)was able to simplify the threshold optimization process to create a weed map,which simulated the fluid flowing from high pressure to low pressure,but it is time consuming and often converges ***,an explosion mechanism and a twophase optimization were introduced to improve the FSO-based segmentation *** of segmentation weeds from a corn field at seedling growth stage showed that the IFSO algorithm obtained the best accuracy of 93.3%and the least running time of 0.019 s,compared with the standard PSO,GA,and FSO algorithms.

关键词： Variable-rate herbicide spraying Weed map Fluid search optimization algorithm Otsu

Potential analysis of an automatic transplanting method for healthy potted seedlings using computer vision

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International Journal of Agricultural and Biological Engineering 2021年第6期14卷 162-168页

作者： Xin Jin Lumei Tang Jiangtao Ji Chenglin wang shengsheng wang College of Agricultural Equipment Engineering Henan University of Science and TechnologyLuoyang 471003China School of Intelligent Manufacturing Engineering Chongqing University of Arts and SciencesYongchuanChongqing 402160China Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province Luoyang 471003China

Healthy seedlings transplanting is an important process in the production of vegetables and economic crops,and the transplanting quality directly affects crop *** seedlings transplanting can improve the transplanting efficiency of *** developed a physical prototype of potted seedling automatic transplanting with a conveyor and a transplanting end-effector in the previous *** work proposed an automatic transplanting method of healthy potted seedlings,which mainly included a detection part of seedlings growth status and a visual servo control part with the purpose of automatic transplanting seedlings *** seedlings and the tray cell were simultaneously detected for identifying healthy seedlings,damaged seedlings and empty cells using a machine vision algorithm when the tray was moving on the conveyor *** visual servo model was applied to enable the collaborative operation of the machine vision and the end-effector for determining the position and attitude of grasping *** experimental results showed that the accuracy rates of the identification of empty tray cells,healthy seedling and unhealthy seedling were 96.42%,98.77%and 89.95%,*** the successful identification of the healthy seedling,the accuracy rate of grasping seedling was 96.38%.It implied that our proposed method can effectively transplant seedlings.

关键词： seedling recognition automatic transplanting computer vision transplanting system

Hybrid Optimization Algorithm Based on Wolf Pack Search and Local Search for Solving Traveling Salesman Problem

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Journal of Shanghai Jiaotong university(Science) 2019年第1期24卷 41-47页

作者： DONG Ruyi wang shengsheng wang Guangyao wang Xinying College of Computer Science and Technology Jilin University Jilin Vocational College of Industry and Technology College of Computer Science and Engineering Changchun University of Technology

Traveling salesman problem(TSP) is one of the typical NP-hard problems, and it has been used in many engineering applications. However, the previous swarm intelligence(SI) based algorithms for TSP cannot coordinate with the exploration and exploitation abilities and are easily trapped into local optimum. In order to deal with this situation, a new hybrid optimization algorithm based on wolf pack search and local search(WPS-LS)is proposed for TSP. The new method firstly simulates the predatory process of wolf pack from the broad field to a specific place so that it allows for a search through all possible solution spaces and prevents wolf individuals from getting trapped into local optimum. Then, local search operation is used in the algorithm to improve the speed of solving and the accuracy of solution. The test of benchmarks selected from TSPLIB shows that the results obtained by this algorithm are better and closer to the theoretical optimal values with better robustness than those obtained by other methods.

关键词： traveling salesman problem(TSP) swarm intelligence(SI) wolf pack search(WPS) combinatorial optimization

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Method for the fruit tree recognition and navigation in complex environment of an agricultural robot

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International Journal of Agricultural and Biological Engineering 2024年第2期17卷 221-229页

作者： Xiaolin Xie Yuchao Li Lijun Zhao Xin Jin shengsheng wang Xiaobing Han College of Agricultural Equipment Engineering Henan University of Science and TechnologyLuoyang 471003HenanChina Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province Luoyang 471003HenanChina Longmen Laboratory Luoyang 471003HenanChina College of Intelligent and Manufacturing Engineering Chongqing University of Arts and SciencesChongqing 402160China

To realize the visual navigation of agricultural robots in the complex environment of orchards,this study proposed a method for fruit tree recognition and navigation based on *** YOLOv5s model was selected and trained to identify the trunks of the left and right rows of fruit trees;the quadratic curve was fitted to the bottom center of the fruit tree recognition box,and the identified fruit trees were divided into left and right columns by using the extreme value point of the quadratic curve to obtain the left and right rows of fruit trees;the straight-line equation of the left and right fruit tree rows was further solved,the median line of the two straight lines was taken as the expected navigation path of the robot,and the path tracing navigation experiment was carried out by using the improved LQR control *** experimental results show that under the guidance of the machine vision system and guided by the improved LQR control algorithm,the lateral error and heading error can converge quickly to the desired navigation path in the four initial states of[0 m,−0.34 rad],[0.10 m,0.34 rad],[0.15 m,0 rad]and[0.20 m,−0.34 rad].When the initial speed was 0.5 m/s,the average lateral error was 0.059 m and the average heading error was 0.2787 rad for the navigation trials in the four different initial *** average driving was 5.3 m into the steady state,the average value of steady state lateral error was 0.0102 m,the average value of steady state heading error was 0.0253 rad,and the average relative error of the robot driving along the desired navigation path was 4.6%.The results indicate that the navigation algorithm proposed in this study has good robustness,meets the operational requirements of robot autonomous navigation in orchard environment,and improves the reliability of robot driving in orchard.

关键词： fruit tree recognition visual navigation YOLOv5 complex environments orchards