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2019 IEEE Symposium Series on Computational Intelligence (SSCI)最新文献

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Domination-Based Ordinal Regression for Expensive Multi-Objective Optimization 基于支配的有序回归的昂贵多目标优化
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9002828
Xunzhao Yu, X. Yao, Yan Wang, Ling Zhu, Dimitar Filev
{"title":"Domination-Based Ordinal Regression for Expensive Multi-Objective Optimization","authors":"Xunzhao Yu, X. Yao, Yan Wang, Ling Zhu, Dimitar Filev","doi":"10.1109/SSCI44817.2019.9002828","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9002828","url":null,"abstract":"Most surrogate-assisted evolutionary algorithms save expensive evaluations by approximating fitness functions. However, many real-world applications are high-dimensional multi-objective expensive optimization problems, and it is difficult to approximate their fitness functions accurately using a very limited number of fitness evaluations. This paper proposes a domination-based ordinal regression surrogate, in which a Kriging model is employed to learn the domination relationship values and to approximate the ordinal landscape of fitness functions. Coupling with a hybrid surrogate management strategy, the solutions with higher probabilities to dominate others are selected and evaluated in fitness functions. Our empirical studies on the DTLZ testing functions demonstrate that the proposed algorithm is more efficient when compared with other state-of-the-art expensive multi-objective optimization methods.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"26-27 1-3 1","pages":"2058-2065"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78306713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Evolving Ensembles of Routing Policies using Genetic Programming for Uncertain Capacitated Arc Routing Problem 基于遗传规划的不确定电容弧线路由策略演化集成
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9002749
Shaolin Wang, Yi Mei, John Park, Mengjie Zhang
{"title":"Evolving Ensembles of Routing Policies using Genetic Programming for Uncertain Capacitated Arc Routing Problem","authors":"Shaolin Wang, Yi Mei, John Park, Mengjie Zhang","doi":"10.1109/SSCI44817.2019.9002749","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9002749","url":null,"abstract":"The Uncertain Capacitated Arc Routing Problem (UCARP) has a wide range of real-world applications. Genetic Programming Hyper-heuristic (GPHH) approaches have shown success in solving UCARP to evolve routing policies that generate routes in real time. However, existing GPHH approaches still have a drawback. Despite the effectiveness in many benchmarks, the single routing policy evolved by GPHH is too complex to interpret. On the other hand, the users need to be able to understand the evolved routing policies to feel confident to use them. In this paper, we aim to employ three ensemble methods, BaggingGP, BoostingGP and Cooperative Co-evolution GP (CCGP) to evolve a group of interpretable routing policies. The ensemble can be used to compare with single complex routing policy from GPHH. Experiment studies show that CCGP significantly outperformed BaggingGP and BoostingGP, and can generate much smaller and simpler routing policies to form ensembles with comparable test performance as the routing policy evolved by SimpleGP. This demonstrates the potential of improving the interpretability issue of GPHH using ensemble methods.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"20 1","pages":"1628-1635"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72906817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Toward Human-like Billiard AI Bot Based on Backward Induction and Machine Learning 基于逆向归纳和机器学习的仿人台球人工智能机器人研究
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9003085
Kuei Gu Tung, Sheng Wen Wang, Wen-Kai Tai, Der-Lor Way, Chinchen Chang
{"title":"Toward Human-like Billiard AI Bot Based on Backward Induction and Machine Learning","authors":"Kuei Gu Tung, Sheng Wen Wang, Wen-Kai Tai, Der-Lor Way, Chinchen Chang","doi":"10.1109/SSCI44817.2019.9003085","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9003085","url":null,"abstract":"A human-like billiard AI bot approach is proposed in this paper. We analyzed actual game records of human players to obtain feature vectors. The Backward Induction algorithm and machine learning are then proposed to imitate decisions by human players. A run-out sequence is searched backwardly with the assists from heuristics and predictions of neural network models. Through the planning process, a strike unit is found to help guide the physics simulator. With our AI suggestion of strategies, it avoids being over-dependent on the robust and precise physics simulation. Also, we defined an appropriate approach to gauge the human likeness of AI and evaluate our proposed methods. The experimental results show that our method overall is more similar to the way how human players play than that of original AI.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"86 1","pages":"924-932"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73152247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Computer Vision for Detecting and Measuring Multicellular Tumor Shperoids of Prostate Cancer 前列腺癌多细胞类肿瘤的计算机视觉检测与测量
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9002908
Alex Wojaczek, Regina-Veronicka Kalaydina, Mohammed Gasmallah, M. Szewczuk, F. Zulkernine
{"title":"Computer Vision for Detecting and Measuring Multicellular Tumor Shperoids of Prostate Cancer","authors":"Alex Wojaczek, Regina-Veronicka Kalaydina, Mohammed Gasmallah, M. Szewczuk, F. Zulkernine","doi":"10.1109/SSCI44817.2019.9002908","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9002908","url":null,"abstract":"We present a deep learning model to apply computer vision to detect prostate cancer spheroid cultures and calculate their volume. Multicellular tumour spheroids, or simply spheroids, represent a three-dimensional in vitro model of cancer. Spheroids are being increasingly used in drug discovery due to their superior ability to mimic the tumor microenvironment compared to monolayer cell cultures. A reduction in spheroid size in response to treatment with anticancer agents is indicative of the success of the therapy. As such, accurate spheroid detection and volume estimation is critical in assays involving spheroids. Automating spheroid detection and measurement reduces manual labor, laboratory costs, and research time. Our system is implemented using Darkflow YOLOv2, a single-phase object detector, based on a twenty-four-layer convolutional neural network. The network is trained on the custom data of biochemically-generated spheroids and their corresponding images, which are then bound and detected with an F1-score of 76% and an IoU of 69%. Volume calculations applied to the identified spheroids resulted in a high volume estimation accuracy with only 3.99% average error.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"54 1","pages":"563-569"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80425188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Efficient Methods for Agile Earth Observation Satellite Scheduling 敏捷对地观测卫星调度的有效方法
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9003056
Xiaoyu Zhao, Zhaohui Wang, Jimin Lv, Yingwu Chen
{"title":"Efficient Methods for Agile Earth Observation Satellite Scheduling","authors":"Xiaoyu Zhao, Zhaohui Wang, Jimin Lv, Yingwu Chen","doi":"10.1109/SSCI44817.2019.9003056","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9003056","url":null,"abstract":"Agile Earth observation satellite (AEOS) scheduling is a complex optimization problem with longer visible time and Time-dependent transition time constraint. We address one method to transform the AEOS scheduling problem to Maximum weight independent set (MWIS) problem to reduce the difficulty of modeling and solving. We also propose reduction and decomposition strategy to reduce the scale of the problem. Experiments proved IP model established by these methods can get optimal solution of the problem, whose size is larger than previous research. Additional, iterated local search hybrid with Variable neighborhood search (VNS-ILS) is designed to solve MWIS problem from AEOS scheduling. The proposed algorithm almost increases all solution quality than ALNS and ALNS-TS adopting in previous research for AEOS scheduling.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"53 1","pages":"3158-3164"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81260786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Study of the Naïve Objective Space Normalization Method in MOEA/D Naïve MOEA/D目标空间归一化方法研究
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9002938
Linjun He, Yang Nan, Ke Shang, H. Ishibuchi
{"title":"A Study of the Naïve Objective Space Normalization Method in MOEA/D","authors":"Linjun He, Yang Nan, Ke Shang, H. Ishibuchi","doi":"10.1109/SSCI44817.2019.9002938","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9002938","url":null,"abstract":"Complex Pareto fronts with objectives in different scales usually appear in real-world multi-objective optimization problems. So as to treat different objectives equally, the naïve normalization method is frequently used due to its simplicity in calculating the estimated ideal and nadir points (i.e., without generating a hyperplane). By directly making use of information from the obtained solutions, the estimated ideal point and the estimated nadir point are obtained. However, the naïve normalization method has rarely been investigated. Moreover, its formulation is often different in each study in the literature. In this paper, we first show four different formulations of the naïve normalization. They are based on different estimation mechanisms of the ideal point and the nadir point. Next we investigate the effect of each formulation on the performance of MOEA/D. Our results show that the search behavior of MOEA/D is significantly impacted due to the choice of a formulation of the naïve normalization method. Finally we suggest the most effective formulation of the naïve normalization method for MOEA/D.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"60 1","pages":"1834-1840"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87637265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
A Bayesian Discrete Optimization Algorithm for Permutation Based Combinatorial Problems 基于排列组合问题的贝叶斯离散优化算法
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9002675
Jianming Zhang, Xifan Yao, Min Liu, Yan Wang
{"title":"A Bayesian Discrete Optimization Algorithm for Permutation Based Combinatorial Problems","authors":"Jianming Zhang, Xifan Yao, Min Liu, Yan Wang","doi":"10.1109/SSCI44817.2019.9002675","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9002675","url":null,"abstract":"Bayesian optimization (BO) is a versatile and robust global optimization method under uncertainty. However, most of the BO algorithms were developed for problems with only continuous variables. For practical engineering optimization, discrete variables are also prevalent. BO methods based on Gaussian process (GP) surrogates also suffers from the curse-of-dimensionality problem. To address these challenges, in this paper, a Bayesian discrete optimization algorithm is introduced to solve permutation-based combinatorial problems. A new kernel function is developed based on position distances for permutation. To improve the efficiency and scalability of the algorithm, a sparse GP model based on inducing points is further developed, where the simulated annealing algorithm is applied to select inducing points. The new algorithm is demonstrated and tested with the production scheduling problem for additive manufacturing. Experimental results show that the proposed algorithm can find a better solution with limited evaluations than state-of-the-art algorithms.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"35 1","pages":"874-881"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89002294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Distributed Collision-Avoidance Formation Control: A Velocity Obstacle-Based Approach 分布式避碰编队控制:一种基于速度障碍的方法
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9003159
Yifan Hu, Han Yu, Yang Zhong, Yuezu Lv
{"title":"Distributed Collision-Avoidance Formation Control: A Velocity Obstacle-Based Approach","authors":"Yifan Hu, Han Yu, Yang Zhong, Yuezu Lv","doi":"10.1109/SSCI44817.2019.9003159","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9003159","url":null,"abstract":"This paper proposes a discrete-time algorithm for formation control of multi-agent systems with collision avoidance, where the agents’ velocity and steering constraints are also considered. To ensure the collision avoidance, the velocity obstacle and reciprocal velocity obstacle methods are introduced to modify the distributed formation algorithm, where each agent uses velocity obstacle method to avoid collision with obstacles, and reciprocal velocity obstacle method to avoid collision with other agents. In this sense, each agent has the ability to pass through complex obstacle environments by autonomously changing prefer velocity. Simulation results show that the proposed algorithm can achieve formation task and meanwhile guarantee collision avoidance.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"27 1","pages":"1994-2000"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89057953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Semi-supervised Image Segmentation Based on K- means Algorithm and Random Walk 基于K均值算法和随机漫步的半监督图像分割
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9003175
Cai Xiumei, Bian Jingwei, Wang Yan, Cui Qiaoqiao
{"title":"Semi-supervised Image Segmentation Based on K- means Algorithm and Random Walk","authors":"Cai Xiumei, Bian Jingwei, Wang Yan, Cui Qiaoqiao","doi":"10.1109/SSCI44817.2019.9003175","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9003175","url":null,"abstract":"Semi-supervised image segmentation is a process of classifying unlabeled pixels using known labeling information. In order to realize image segmentation, solve the problem of setting a large number of seed points in the random walk algorithm, and solve the local optimization problem in the K- means algorithm, this paper proposes a semi-supervised image segmentation algorithm based on the K-means algorithm and random walk. Firstly, the K-means algorithm is used for clustering to determine the clustering center, then, the transfer probability from each unlabeled pixel to the seed point is calculated based on the random walk algorithm, and the image segmentation is completed according to the transfer probability. It can be seen from the experimental results that the segmentation accuracy is greatly improved and the effectiveness of this paper is verified.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"61 12","pages":"2853-2856"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91439748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Fast Algorithm for HEVC Screen Content Coding HEVC屏幕内容编码的快速算法
2019 IEEE Symposium Series on Computational Intelligence (SSCI) Pub Date : 2019-12-01 DOI: 10.1109/SSCI44817.2019.9002825
H. Tang, Y. Duan, L. Sun, Yi ran Li
{"title":"A Fast Algorithm for HEVC Screen Content Coding","authors":"H. Tang, Y. Duan, L. Sun, Yi ran Li","doi":"10.1109/SSCI44817.2019.9002825","DOIUrl":"https://doi.org/10.1109/SSCI44817.2019.9002825","url":null,"abstract":"As a high efficiency video coding (HEVC) extension, screen content coding (SCC) has a significant effect in the compressed screen content, but causes a problem encoder calculates a higher complexity. This paper proposes a fast decision method based on HEVC screen content coding. The image content is divided into a natural coding unit (NCU) and a screen coding unit (SCU). The image gradients of different properties are different, and the gini impurity classification gradient value is used to speed up the encoding speed. The experimental results show that under the frame configuration of HM-15.0 SCM-2.0, the method can save about 41.4% of the encoder time.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"4 1","pages":"2921-2925"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83722888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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