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International Journal of Cognitive Informatics and Natural Intelligence最新文献

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Hybrid Bacteria Foraging Algorithm with PSO and DE algorithm for optimal Cluster head selection in Wireless Sensor Networks 基于PSO和DE算法的混合细菌觅食算法在无线传感器网络中的最优簇头选择
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.301206
{"title":"Hybrid Bacteria Foraging Algorithm with PSO and DE algorithm for optimal Cluster head selection in Wireless Sensor Networks","authors":"","doi":"10.4018/ijcini.301206","DOIUrl":"https://doi.org/10.4018/ijcini.301206","url":null,"abstract":"Network lifetime and energy constraint are the main issues for the applications of Wireless Sensor Network. Sensor nodes spend more energy in the communication process and affect the network lifetime. Clustering is the technique for choosing the optimal cluster head from the clusters. LEACH-C is the clustering protocol in WSN. BFA is applied in the LEACH-C protocol to form the optimal clusters. This optimization obtains more number of steps in the tumbling process and reaches the global optimum solution very slowly. This method directly affects the network lifetime. The above limitations are overcome by introducing the hybrid approach of Bacteria foraging algorithm by integrating the PSO and DE is applied in LEACH-C algorithm for finding the optimal cluster head. The best foraging solution utilized in the chemotactic behavior of the bacterium by using PSO and DE algorithm. The proposed methodology increases by 66% and 77% of the alive nodes when compared to FA and BFPSO.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47874611","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
The Recognition of Microscopic Images of Ceramics Incorporating Blockchain Technology 基于区块链技术的陶瓷显微图像识别
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.296728
Yuanxin Qiu, Xing Xu, Xien Cheng
{"title":"The Recognition of Microscopic Images of Ceramics Incorporating Blockchain Technology","authors":"Yuanxin Qiu, Xing Xu, Xien Cheng","doi":"10.4018/ijcini.296728","DOIUrl":"https://doi.org/10.4018/ijcini.296728","url":null,"abstract":"Having summarized the previous research on ceramic identification and the anti-counterfeiting, the authors propose a ceramic identification system that combines computer vision algorithms with blockchain technology. The system uses irregular pores on microscopic images of ceramic surfaces as image features, and it applies the SIFT(Scale-invariant feature transform) algorithm to extract feature. The images and feature vector sets are then stored by IPFS(Inter-planetary File System). When a consumer needs to authenticate a ceramic product, it is only necessary to take a microscopic image of the specified location, and then the SIFT algorithm will compare the picture with the data stored in the IPFS network, and was previously obtained through the records on a blockchain network, the matching result then determines whether the photographed ceramic is one of those already recorded. Experimental show that the matching results can be used as a strong basis for identifying the origin of ceramic products.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88368881","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
Policy Communication Through Artificial Intelligence in China and Western Countries 基于人工智能的中西方政策沟通
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.307154
Yuyun Zhang
{"title":"Policy Communication Through Artificial Intelligence in China and Western Countries","authors":"Yuyun Zhang","doi":"10.4018/ijcini.307154","DOIUrl":"https://doi.org/10.4018/ijcini.307154","url":null,"abstract":"Communication has become the crucial key to a success of public policy both in China and Western countries. After more than thirty years of development, China and Western countries have made fruitful achievements. We made a comparative review of policy communication studies in three aspects: general situations, topics and theoretical prospects. Firstly, the trend of policy communication research from both sides are positive, and it focuses on the new topics brought by the development of artificial intelligence. Secondly, by applying artificial intelligence technology to the research, it is concluded that scholars focus on three topics: communication mechanism, crisis communication and monetary policy communication. Thirdly, policy communication studies have provided us with rich practical materials and useful theoretical exploration, but there is still a lack of attention to Chinese advanced policy communication practices and a profound understanding of the challenges in the context of artificial intelligence which is the direction worthy of scholars striving in in the future.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47941750","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
Recognition of Air Passengers' Willingness to Pay for Seat Selection for Imbalanced Data Based on Improved XGBoost 基于改进XGBoost的不平衡数据对航空乘客选座意愿的识别
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.312249
Baiyu Hong, Xiaolong Ma, Weining Tang, Zhangguo Shen
{"title":"Recognition of Air Passengers' Willingness to Pay for Seat Selection for Imbalanced Data Based on Improved XGBoost","authors":"Baiyu Hong, Xiaolong Ma, Weining Tang, Zhangguo Shen","doi":"10.4018/ijcini.312249","DOIUrl":"https://doi.org/10.4018/ijcini.312249","url":null,"abstract":"Passenger-paid seat selection is one of the important sources of ancillary revenue for airlines, and machine learning-based willingness-to-pay identification is of great practicality for airlines to accurately tap potential willing passengers. However, affected by periodic statistical errors, air passenger order data often has some problems such as high noise, high latitude, and unbalanced category. In view of this, this paper proposes a method for identifying air passengers' willingness to pay for seat selection based on improved XGBoost, which is improved and integrated from three stages: data, feature, and algorithm. The feasibility of the proposed multi-stage improved integration method is verified by real airline passenger dataset, and the experimental results show that the proposed improved method has better classification effect when compared with the classical six imbalance classification models, which provides a basis for accurate marketing of airline paid seat selection programs.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47062227","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
Computing Offloading Decision Based on Adaptive Estimation of Distribution Algorithm in Internet of Vehicles 基于自适应估计分布算法的车联网卸载决策计算
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.312250
F. Yu, Meijia Chen, Bolin Yu
{"title":"Computing Offloading Decision Based on Adaptive Estimation of Distribution Algorithm in Internet of Vehicles","authors":"F. Yu, Meijia Chen, Bolin Yu","doi":"10.4018/ijcini.312250","DOIUrl":"https://doi.org/10.4018/ijcini.312250","url":null,"abstract":"Aimed to improve the efficiency of computing offloading in internet of vehicles (IoV), a collaborative multi-task computing offloading decision mechanism with adaptive estimation of distribution algorithm for MEC-IoV was proposed in this paper. The algorithm considered the energy and time consumption as well as priority among different tasks. It presented a local search strategy and an adaptive learning rate according to the characteristics of the problem to improve the estimation of distribution algorithm. Experimental results show that compared with other offloading strategies, the proposed offloading strategy has obvious effects on the total cost optimization; the solutions quality of AEDA is 86.6% of PSO and 67.3% of GA.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47147323","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: 1
Corn Disease Detection Based on an Improved YOLOX-Tiny Network Model 基于改进YOLOX微网络模型的玉米病害检测
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.309990
Shanni Li, Zhensheng Yang, Huabei Nie, Xiao Chen
{"title":"Corn Disease Detection Based on an Improved YOLOX-Tiny Network Model","authors":"Shanni Li, Zhensheng Yang, Huabei Nie, Xiao Chen","doi":"10.4018/ijcini.309990","DOIUrl":"https://doi.org/10.4018/ijcini.309990","url":null,"abstract":"In order to detect corn diseases accurately and quickly and reduce the impact of corn diseases on yield and quality, this paper proposes an improved object detection network named YOLOX-Tiny, which fuses convolutional attention module (CBAM), mixup data enhancement strategy, and center IOU loss function. The detection network uses the CSPNet network model as the backbone network and adds the CBAM to the feature pyramid network (FPN) of the structure, which re-assigns the feature maps' weight of different channels to enhance the extraction of deep information from the structure. The performance evaluation and comparison results of the methods show that the improved YOLOX-Tiny object detection network can effectively detect three common corn diseases, such as cercospora grayspot, northern blight, and commonrust. Compared with the traditional neural network models (90.89% of VGG-16, 97.32% of YOLOv4-tiny, 97.85% of YOLOX-Tiny, 97.91% of ResNet-50, and 97.31% of Faster RCNN), the presented improved YOLOX-Tiny network has higher accuracy.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45164426","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: 1
A Many-Objective Practical Swarm Optimization Based on Mixture Uniform Design and Game Mechanism 基于混合均匀设计和博弈机制的多目标实用群优化
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.301203
Chen Yan, Cai Mengxiang, Zheng Mingyong, Kangshun Li
{"title":"A Many-Objective Practical Swarm Optimization Based on Mixture Uniform Design and Game Mechanism","authors":"Chen Yan, Cai Mengxiang, Zheng Mingyong, Kangshun Li","doi":"10.4018/ijcini.301203","DOIUrl":"https://doi.org/10.4018/ijcini.301203","url":null,"abstract":"In recent years, multi-objective optimization algorithms, especially many-objective optimization algorithms, have developed rapidly and effectively.Among them, the algorithm based on particle swarm optimization has the characteristics of simple principle, few parameters and easy implementation. However, these algorithms still have some shortcomings, but also face the problems of falling into the local optimal solution, slow convergence speed and so on. In order to solve these problems, this paper proposes an algorithm called MUD-GMOPSO, A Many-Objective Practical Swarm Optimization based on Mixture Uniform Design and Game mechanism. In this paper, the two improved methods are combined, and the convergence speed, accuracy and robustness of the algorithm are greatly improved. In addition, the experimental results show that the algorithm has better performance than the four latest multi-objective or high-dimensional multi-objective optimization algorithms on three widely used benchmarks: DTLZ, WFG and MAF.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90746073","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
Dual-Population Co-Evolution Multi-Objective Optimization Algorithm and Its Application: Power Allocation Optimization of Mobile Base Stations 双种群协同进化多目标优化算法及其应用:移动基站功率分配优化
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.296258
Bo Yu, Fahui Gu
{"title":"Dual-Population Co-Evolution Multi-Objective Optimization Algorithm and Its Application: Power Allocation Optimization of Mobile Base Stations","authors":"Bo Yu, Fahui Gu","doi":"10.4018/ijcini.296258","DOIUrl":"https://doi.org/10.4018/ijcini.296258","url":null,"abstract":"In the multi-objective optimization algorithm, the parameter strategy has a huge impact on the performance of the algorithm, and it is difficult to set a set of parameters with excellent distribution and convergence performance in the actual optimization process. Based on the MOEA/D algorithm framework, this paper construct an improved dual-population co-evolution MOEA/D algorithm by adopt the idea of dual-population co-evolution. The simulation test of the benchmark functions shows that the proposed dual-population co-evolution MOEA/D algorithm have significant improvements in IGD and HV indicators compare with three other comparison algorithms. Finally, the application of the LTE base station power allocation model also verifies the effectiveness of the proposed algorithm.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86869713","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
Exploring the Relationship Between Conception of Language Learning and Foreign Language Learning Burnout: An Empirical Study Among University Students 探索语言学习观念与外语学习倦怠的关系:一项大学生的实证研究
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.309133
Minghui Yang, Yuhui Zhai
{"title":"Exploring the Relationship Between Conception of Language Learning and Foreign Language Learning Burnout: An Empirical Study Among University Students","authors":"Minghui Yang, Yuhui Zhai","doi":"10.4018/ijcini.309133","DOIUrl":"https://doi.org/10.4018/ijcini.309133","url":null,"abstract":"This study explores the relationship between college students’ conception of language learning and foreign language learning burnout and tries to solve the following problems: How does learners’ conception of language learning affect their English learning burnout? How to relieve English learning burnout? Data were collected through two questionnaires, English learning burnout and conception of language learning, among 363 non-English majors in two universities in central part of China. The findings provide empirical evidence linking college students’ conception of language learning with their English learning burnout: “Testing” is the key factor that leading to burnout in English learning, which positively predicts “Exhaustion”, “Apathy” and “Reduced self-efficacy”; “Memorizing” positively influences “Reduced Self-efficacy” and negatively predicts “Apathy”; “Language knowledge” negatively predicts “Exhaustion” and “Understanding and Seeing in a new way” negatively predicts “Apathy”.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80129042","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: 1
A Hybrid Learning Particle Swarm Optimization With Fuzzy Logic for Sentiment Classification Problems 基于模糊逻辑的混合学习粒子群算法在情感分类中的应用
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2022-01-01 DOI: 10.4018/ijcini.314782
Jiyuan Wang, Kaiyue Wang, X. Yan, Chanjuan Wang
{"title":"A Hybrid Learning Particle Swarm Optimization With Fuzzy Logic for Sentiment Classification Problems","authors":"Jiyuan Wang, Kaiyue Wang, X. Yan, Chanjuan Wang","doi":"10.4018/ijcini.314782","DOIUrl":"https://doi.org/10.4018/ijcini.314782","url":null,"abstract":"Methods based on deep learning have great utility in the current field of sentiment classification. To better optimize the setting of hyper-parameters in deep learning, a hybrid learning particle swarm optimization with fuzzy logic (HLPSO-FL) is proposed in this paper. Hybrid learning strategies are divided into mainstream learning strategies and random learning strategies. The mainstream learning strategy is to define the mainstream particles in the cluster and build a scale-free network through the mainstream particles. The random learning strategy makes full use of historical information and speeds up the convergence of the algorithm. Furthermore, fuzzy logic is used to control algorithm parameters to balance algorithm exploration and exploration performance. HLPSO-FL has completed comparison experiments on benchmark functions and real sentiment classification problems respectively. The experimental results show that HLPSO-FL can effectively complete the hyperparameter optimization of sentiment classification problem in deep learning and has strong convergence.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45634233","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: 1
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