Pub Date : 2021-09-22DOI: 10.1109/CICN51697.2021.9574694
D. Tomar, Megha Kamble
Nowadays higher demands of lightweight mobile devices for monitoring critical situation such as weather, tsunami, earth quick and rural area where direct communication not possible. Those area DTN mobile communications play important role to provide message exchange between devices through limited capacity (channel, memory, processing). Due to exhaustive demand of DTN mobile communication, concurrently multiple nodes exchange the message from one location to another through lightweight capable node that arises the problem of congestion, in this paper investigate various existing approach to resolve the network related issue to enhance the performance of delay tolerant network (DTN). Those existing approach give the roadmap to further enhancement of DTN network for smooth working in real time communication in rural area where disseminated connectivity. In the paper we also design new congestion detection and prevention method using collaborative methodologies such as input and output dependency retrieval, energy utilization and fuzzy rule definition and provide lightweight solution to the DTN for improving the efficiency of network where nodes are configure in limited capacity. In future we analyse those work through the network simulator −2 and measure the performance of the network.
{"title":"Investigation and Designing for Network Congestion Detection and Prevention in DTN","authors":"D. Tomar, Megha Kamble","doi":"10.1109/CICN51697.2021.9574694","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574694","url":null,"abstract":"Nowadays higher demands of lightweight mobile devices for monitoring critical situation such as weather, tsunami, earth quick and rural area where direct communication not possible. Those area DTN mobile communications play important role to provide message exchange between devices through limited capacity (channel, memory, processing). Due to exhaustive demand of DTN mobile communication, concurrently multiple nodes exchange the message from one location to another through lightweight capable node that arises the problem of congestion, in this paper investigate various existing approach to resolve the network related issue to enhance the performance of delay tolerant network (DTN). Those existing approach give the roadmap to further enhancement of DTN network for smooth working in real time communication in rural area where disseminated connectivity. In the paper we also design new congestion detection and prevention method using collaborative methodologies such as input and output dependency retrieval, energy utilization and fuzzy rule definition and provide lightweight solution to the DTN for improving the efficiency of network where nodes are configure in limited capacity. In future we analyse those work through the network simulator −2 and measure the performance of the network.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130050456","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}
Pub Date : 2021-09-22DOI: 10.1109/CICN51697.2021.9574687
F. Meng, Wenhui Wang, Songbin Bao
Formulaic language plays an indispensable role in academic English writing and translation. To provide a convenient environment for Chinese learners to acquire the English formulaic language, an English-Chinese bilingual parallel corpus of academic formulaic language with 1643 sentence pairs is constructed. This paper introduces the construction method of the corpus, discusses the teaching application scenarios matching with its functions, designs a cross-contrast experiment, and verifies the convenience and effectiveness of the system. Using various retrieval channels and abundant corpus provided by the system, learners could master a large number of academic formulaic languages imperceptibly in their daily study. At the same time, the system can also provide data sources for computer-aided translation and other research on formulaic language.
{"title":"The Construction and Application of An English-Chinese Corpus of Academic Formulaic language","authors":"F. Meng, Wenhui Wang, Songbin Bao","doi":"10.1109/CICN51697.2021.9574687","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574687","url":null,"abstract":"Formulaic language plays an indispensable role in academic English writing and translation. To provide a convenient environment for Chinese learners to acquire the English formulaic language, an English-Chinese bilingual parallel corpus of academic formulaic language with 1643 sentence pairs is constructed. This paper introduces the construction method of the corpus, discusses the teaching application scenarios matching with its functions, designs a cross-contrast experiment, and verifies the convenience and effectiveness of the system. Using various retrieval channels and abundant corpus provided by the system, learners could master a large number of academic formulaic languages imperceptibly in their daily study. At the same time, the system can also provide data sources for computer-aided translation and other research on formulaic language.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124421622","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}
Pub Date : 2021-09-22DOI: 10.1109/CICN51697.2021.9574683
G. Soni
The various advanced applications of 5G based wireless communications include autonomous self-driven cars, telemedicine, smart spaces (e.g., home, office, etc.), sensor networks, high speed trains, smart cities, and many more [9]. For such data intensive wireless communications, only radio frequency (RF) based wireless systems cannot meet the desired demands because RF band is susceptible to interference, has limited capacity, and requires a heavy license fee to use the spectrum [10]. Hence, other portions of the electromagnetic (EM) spectrum and new technologies are required to be considered for fulfilling the demands of wireless communication systems in the near future. One such alternative solution is Free Space Optics (FSO) which is an optical wireless communication (OWC) based technology. The FSO not only has many advantages but also hampered by some atmospheric conditions, which degrades the link performance. This paper reviews the FSO link design and effect of different atmospheric condition like- fog, scintillation, turbulence, rain etc. This paper studies the system performance of an optical ISL which is proposed between satellites over Low Earth Orbit (LEO). In this study, the proposed link is simulated to obtain the maximum allowable data rate and minimum bit error rate over different distances. The system performance is improved by investigating its dependency on the photo detector type, operating wavelength, transmitted optical power, RZ and NRZ schemes.
{"title":"Performance Evaluation and Analysis of an WoC Based Inter Satellite Link over the Low Earth Orbit","authors":"G. Soni","doi":"10.1109/CICN51697.2021.9574683","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574683","url":null,"abstract":"The various advanced applications of 5G based wireless communications include autonomous self-driven cars, telemedicine, smart spaces (e.g., home, office, etc.), sensor networks, high speed trains, smart cities, and many more [9]. For such data intensive wireless communications, only radio frequency (RF) based wireless systems cannot meet the desired demands because RF band is susceptible to interference, has limited capacity, and requires a heavy license fee to use the spectrum [10]. Hence, other portions of the electromagnetic (EM) spectrum and new technologies are required to be considered for fulfilling the demands of wireless communication systems in the near future. One such alternative solution is Free Space Optics (FSO) which is an optical wireless communication (OWC) based technology. The FSO not only has many advantages but also hampered by some atmospheric conditions, which degrades the link performance. This paper reviews the FSO link design and effect of different atmospheric condition like- fog, scintillation, turbulence, rain etc. This paper studies the system performance of an optical ISL which is proposed between satellites over Low Earth Orbit (LEO). In this study, the proposed link is simulated to obtain the maximum allowable data rate and minimum bit error rate over different distances. The system performance is improved by investigating its dependency on the photo detector type, operating wavelength, transmitted optical power, RZ and NRZ schemes.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122261591","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}
In order to help users to correctly classify garbage and achieve better utilization of garbage resources, this article proposes an intelligent garbage classification system, which includes a cloud server, intelligent classification garbage bins, and mobile smart ends. Using cloud computing, artificial intelligence, image processing, Raspberry Pi design, WeChat mini-program and other technologies, the intelligent classification garbage bin realizes three working modes: manual classification, automatic classification, and compression. In the automatic classification mode, the intelligent classification garbage bin firstly preprocesses the collected garbage images, then uploads the main garbage images to the cloud server for classification, and finally uses the garbage position information provided by the resistive screen on the carrying platform to adjust in real time garbage delivery posture, put the garbage into corresponding part of the garbage bin to prevent the garbage from falling accidentally. The mobile smart end implements multiple functions, for instance, tracing the results of garbage disposal. It has been thoroughly tested that the accuracy of this system for automatic classification reaches 92%, providing a simple and feasible solution for garbage classification.
{"title":"Design and Implementation of Intelligent Garbage Classification System Based on Artificial Intelligence Technology","authors":"Daheng Lin, Zhenglu Chen, Mengmeng Wang, Jiale Zhang, Xinxin Zhou","doi":"10.1109/CICN51697.2021.9574675","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574675","url":null,"abstract":"In order to help users to correctly classify garbage and achieve better utilization of garbage resources, this article proposes an intelligent garbage classification system, which includes a cloud server, intelligent classification garbage bins, and mobile smart ends. Using cloud computing, artificial intelligence, image processing, Raspberry Pi design, WeChat mini-program and other technologies, the intelligent classification garbage bin realizes three working modes: manual classification, automatic classification, and compression. In the automatic classification mode, the intelligent classification garbage bin firstly preprocesses the collected garbage images, then uploads the main garbage images to the cloud server for classification, and finally uses the garbage position information provided by the resistive screen on the carrying platform to adjust in real time garbage delivery posture, put the garbage into corresponding part of the garbage bin to prevent the garbage from falling accidentally. The mobile smart end implements multiple functions, for instance, tracing the results of garbage disposal. It has been thoroughly tested that the accuracy of this system for automatic classification reaches 92%, providing a simple and feasible solution for garbage classification.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128520551","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}
Pub Date : 2021-09-22DOI: 10.1109/CICN51697.2021.9574662
Antony B. Almonacid, Ciro Rodríguez, Yuri Pomachagua, Diego Rodriguez
This research aims to reduce the detection time of the risk of suffering from arterial hypertension by implementing a hybrid model based on the Support Vector Machine (SVM) and Principal Component Analysis (PCA) algorithms. The proposed hybrid model was implemented from the processing of a dataset made up of 70,000 records related to characteristics such as systolic blood pressure, diastolic blood pressure, cholesterol index, glucose index, smoking and sedentary lifestyle. The methodology for the implementation of the hybrid model consisted of the stages of data collection, data exploration, data pre-processing, selection of characteristics, and implementation of the model and the validation of results. As a result of the implementation of the model, a precision level of 72.18% was obtained in relation to the detection of the risk of suffering from arterial hypertension.
{"title":"Hybrid Model based on Support Vector Machine and Principal Component Analysis Applied to Arterial Hypertension Detection","authors":"Antony B. Almonacid, Ciro Rodríguez, Yuri Pomachagua, Diego Rodriguez","doi":"10.1109/CICN51697.2021.9574662","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574662","url":null,"abstract":"This research aims to reduce the detection time of the risk of suffering from arterial hypertension by implementing a hybrid model based on the Support Vector Machine (SVM) and Principal Component Analysis (PCA) algorithms. The proposed hybrid model was implemented from the processing of a dataset made up of 70,000 records related to characteristics such as systolic blood pressure, diastolic blood pressure, cholesterol index, glucose index, smoking and sedentary lifestyle. The methodology for the implementation of the hybrid model consisted of the stages of data collection, data exploration, data pre-processing, selection of characteristics, and implementation of the model and the validation of results. As a result of the implementation of the model, a precision level of 72.18% was obtained in relation to the detection of the risk of suffering from arterial hypertension.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115863144","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}
Pneumonia is an inflammatory condition affecting the small air sacs known as the alveoli present in the lungs. Despite the availability of vaccines for certain types it is known to be one of the leading causes of death across all age groups around the world. Chest X-Ray (CXR) images, blood test or sputum culture are standard techniques primarily used by doctors to confirm their diagnosis but is prone to human error due to huge imbalance between number of potential patients and doctors. Deep learning based computer aided technology with reasonably good accuracy and precision can aid the doctors by eliminating the benign cases. In this paper, a transfer learning based convolutional neural network (CNN) architectures is proposed for classifying CXR images into healthy and pneumonia affected with high accuracy and precision. The proposed method uses three different transfer learning architectures, viz. VGG - 16, VGG - 19 and Inception Resnet V2 for comparison and is found to provide best results with VGG - 19 architecture. An accuracy of 95.82% with 98.55% precision, 96.20% specificity and 95.67% sensitivity are obtained with the help of VGG-19 which is superior to any existing solution known to the authors.
{"title":"Transfer Learning based Detection of Pneumonia from Chest X-Ray Images","authors":"Sai Dheeraj Gummadi, Yeswanth Vootla, Anirban Ghosh, Peddisetty Naga Kartheek, Anjan Krishna Kandimalla","doi":"10.1109/CICN51697.2021.9574689","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574689","url":null,"abstract":"Pneumonia is an inflammatory condition affecting the small air sacs known as the alveoli present in the lungs. Despite the availability of vaccines for certain types it is known to be one of the leading causes of death across all age groups around the world. Chest X-Ray (CXR) images, blood test or sputum culture are standard techniques primarily used by doctors to confirm their diagnosis but is prone to human error due to huge imbalance between number of potential patients and doctors. Deep learning based computer aided technology with reasonably good accuracy and precision can aid the doctors by eliminating the benign cases. In this paper, a transfer learning based convolutional neural network (CNN) architectures is proposed for classifying CXR images into healthy and pneumonia affected with high accuracy and precision. The proposed method uses three different transfer learning architectures, viz. VGG - 16, VGG - 19 and Inception Resnet V2 for comparison and is found to provide best results with VGG - 19 architecture. An accuracy of 95.82% with 98.55% precision, 96.20% specificity and 95.67% sensitivity are obtained with the help of VGG-19 which is superior to any existing solution known to the authors.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121842660","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}
Pub Date : 2021-09-22DOI: 10.1109/CICN51697.2021.9574681
Fanqi Meng, Haochen Sun, Jingdong Wang
In some hard real-time systems, the system has high requirements for program execution time and energy consumption. If the program runs overtime or the energy is exhausted in advance, it will have a significant impact on system security. In order to be able to more accurately predict the WCET and energy consumption of the program and provide support for the subsequent search for the best optimization method that optimizes WCET and the average execution time at the same time, this paper gives a set of feasible methods that can predict the worst execution time and average execution time of the program. On the basis of existing research, the static method of program execution time estimation is integrated with the dynamic method, and the WCET and energy consumption of the program are estimated using the sample program features such as dynamic instruction features, and the L-M (Levenberg-Marquardt) algorithm is used to train neural network. And compared with the traditional regression algorithm, add quantitative indicators and verify the feasibility of the method. The method in this paper can make an accurate prediction of the execution time of the program. The research is helpful to the follow-up development of this field and provides a useful reference and reference for the further optimization of the program.
{"title":"Establish Program WCET and Energy Consumption Prediction Model Based on L-M Algorithm","authors":"Fanqi Meng, Haochen Sun, Jingdong Wang","doi":"10.1109/CICN51697.2021.9574681","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574681","url":null,"abstract":"In some hard real-time systems, the system has high requirements for program execution time and energy consumption. If the program runs overtime or the energy is exhausted in advance, it will have a significant impact on system security. In order to be able to more accurately predict the WCET and energy consumption of the program and provide support for the subsequent search for the best optimization method that optimizes WCET and the average execution time at the same time, this paper gives a set of feasible methods that can predict the worst execution time and average execution time of the program. On the basis of existing research, the static method of program execution time estimation is integrated with the dynamic method, and the WCET and energy consumption of the program are estimated using the sample program features such as dynamic instruction features, and the L-M (Levenberg-Marquardt) algorithm is used to train neural network. And compared with the traditional regression algorithm, add quantitative indicators and verify the feasibility of the method. The method in this paper can make an accurate prediction of the execution time of the program. The research is helpful to the follow-up development of this field and provides a useful reference and reference for the further optimization of the program.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"30 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117275215","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}
Pub Date : 2021-09-22DOI: 10.1109/CICN51697.2021.9574663
G. Soni
FSO is a terrestrial OWC system used for point-to-point communication and operates at near infrared (IR) frequencies (750–1600 nm). It is a laser driven Communication based on line of sight (LOS) enabling technology for the transmission and reception of information carrying light signals through the atmosphere. For the same, it uses light sources and light detectors, i.e., laser diodes and photodiodes, respectively. The real motive behind using FSO is to do away with the cost, time, and effort in laying fiber optic cables without adversely impacting high data rates for transmitting voice, image, text, video, or any other file. In recent years, Free space based optical communication has developed and grown rapidly and has been widely used in applications like satellite laser based communication, radar detection, and other fields. Space optical communication based system includes a TX-RX antenna system and a coupling system. The research of space optical communication system often separates the antenna systems and the coupling system for discussion. When analyzing TX-RX antenna systems, geometric optics is generally used. Based on ancient diffraction theory, the performance of space optical communication systems consisting of a transmitter antenna, receiver antenna, and fiber coupling based systems are analyzed. Besides, several practical situations are also considered such as the defocusing of the TX-RX antenna and the deviation of the fiber. The longer or greater the transmission distance, the greater the effect of diffraction. When the transmission distance is short, the defocusing of the primary mirror will help it improve the transmission efficiency of the given system.
{"title":"Performance Investigation of the Free Space Optics Link based Communication using DOE scheme at 1550nm","authors":"G. Soni","doi":"10.1109/CICN51697.2021.9574663","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574663","url":null,"abstract":"FSO is a terrestrial OWC system used for point-to-point communication and operates at near infrared (IR) frequencies (750–1600 nm). It is a laser driven Communication based on line of sight (LOS) enabling technology for the transmission and reception of information carrying light signals through the atmosphere. For the same, it uses light sources and light detectors, i.e., laser diodes and photodiodes, respectively. The real motive behind using FSO is to do away with the cost, time, and effort in laying fiber optic cables without adversely impacting high data rates for transmitting voice, image, text, video, or any other file. In recent years, Free space based optical communication has developed and grown rapidly and has been widely used in applications like satellite laser based communication, radar detection, and other fields. Space optical communication based system includes a TX-RX antenna system and a coupling system. The research of space optical communication system often separates the antenna systems and the coupling system for discussion. When analyzing TX-RX antenna systems, geometric optics is generally used. Based on ancient diffraction theory, the performance of space optical communication systems consisting of a transmitter antenna, receiver antenna, and fiber coupling based systems are analyzed. Besides, several practical situations are also considered such as the defocusing of the TX-RX antenna and the deviation of the fiber. The longer or greater the transmission distance, the greater the effect of diffraction. When the transmission distance is short, the defocusing of the primary mirror will help it improve the transmission efficiency of the given system.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127289858","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}
Pub Date : 2021-09-22DOI: 10.1109/CICN51697.2021.9574678
Xinxin Zhou, Zhirui Gao, Xueting Yi, Daheng Lin
Aiming at the problem of low accuracy of the Chicken Swarm Optimization Algorithm and falling into the local optimum easily, a self-adaptive dynamic distribution Chicken Swarm Optimization (DCSO) is proposed. Firstly, a dynamic weight strategy is proposed to solve the problem of reduced algorithm accuracy; Secondly, the learning factor of normal distribution is used to solve the problem that the algorithm is easy to fall into the local optimum; Finally, 16 benchmark functions are used to test the performance of the algorithm. And the experimental results show that the improved Chicken Swarm Optimization has better solution accuracy and it can jump out of the local optimum.
{"title":"Chicken Swarm Optimization Algorithm Based on Adaptive Dynamic Distribution","authors":"Xinxin Zhou, Zhirui Gao, Xueting Yi, Daheng Lin","doi":"10.1109/CICN51697.2021.9574678","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574678","url":null,"abstract":"Aiming at the problem of low accuracy of the Chicken Swarm Optimization Algorithm and falling into the local optimum easily, a self-adaptive dynamic distribution Chicken Swarm Optimization (DCSO) is proposed. Firstly, a dynamic weight strategy is proposed to solve the problem of reduced algorithm accuracy; Secondly, the learning factor of normal distribution is used to solve the problem that the algorithm is easy to fall into the local optimum; Finally, 16 benchmark functions are used to test the performance of the algorithm. And the experimental results show that the improved Chicken Swarm Optimization has better solution accuracy and it can jump out of the local optimum.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121068650","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}
Pub Date : 2021-09-22DOI: 10.1109/CICN51697.2021.9574665
Juan Carlos Rivera Rado, C. Rodriguez
The Business Intelligence (BI) tool is a solution that allows organizations to access information that enables them to address and support the complex process of decision making with multiple criteria. We present the results of implementing Business Intelligence tools to contribute to the electrical industry in this article. This article aims to present the Business Intelligence tools that can contribute to the electrical industry, using the literature review as a methodology. As a result, 170 potential articles were obtained. From these articles, 20 were selected as they will be helpful for the development of a Business Intelligence tool to solve the problem of decision making in an electricity distribution company. The conclusion is that the Business Intelligence tools implemented in the industries offer promising proposals and benefits and can be applied in the electrical industry.
{"title":"Business Intelligence Tools Implementing in the Field of Electrical Industry","authors":"Juan Carlos Rivera Rado, C. Rodriguez","doi":"10.1109/CICN51697.2021.9574665","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574665","url":null,"abstract":"The Business Intelligence (BI) tool is a solution that allows organizations to access information that enables them to address and support the complex process of decision making with multiple criteria. We present the results of implementing Business Intelligence tools to contribute to the electrical industry in this article. This article aims to present the Business Intelligence tools that can contribute to the electrical industry, using the literature review as a methodology. As a result, 170 potential articles were obtained. From these articles, 20 were selected as they will be helpful for the development of a Business Intelligence tool to solve the problem of decision making in an electricity distribution company. The conclusion is that the Business Intelligence tools implemented in the industries offer promising proposals and benefits and can be applied in the electrical industry.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126325816","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}
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