Pub Date : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875526
Soukaina Nai, Amal Rifai, A. Sadiq, M'hamed Bakrim
This paper focuses on the concept of e-portfolio in education and its different types. Our objective is to improve the learning level of students and decrease the dropout rate in Morocco by using this tool. Indeed, we have proposed in a previous work. a new participatory tutoring strategy between the Moroccan educational administration and teachers, standardized nationally to ensure equity and quality of training and assistance to students. This strategy is based on the validation of academic skills through a computer system that we plan to design as part of this project. Its role is to use the learner's portfolio in an official framework to ensure the monitoring and development of his or her academic skills. This system must be composed of e-portfolios of evaluation and learning (remediation) of the student. In this work, we will proceed to establish the structure of our software solution by modeling the processes of evaluation and remediation of the learner's academic skills.
{"title":"Preliminary Study Of A Smart Computer System For Scholar Support","authors":"Soukaina Nai, Amal Rifai, A. Sadiq, M'hamed Bakrim","doi":"10.1109/SETIT54465.2022.9875526","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875526","url":null,"abstract":"This paper focuses on the concept of e-portfolio in education and its different types. Our objective is to improve the learning level of students and decrease the dropout rate in Morocco by using this tool. Indeed, we have proposed in a previous work. a new participatory tutoring strategy between the Moroccan educational administration and teachers, standardized nationally to ensure equity and quality of training and assistance to students. This strategy is based on the validation of academic skills through a computer system that we plan to design as part of this project. Its role is to use the learner's portfolio in an official framework to ensure the monitoring and development of his or her academic skills. This system must be composed of e-portfolios of evaluation and learning (remediation) of the student. In this work, we will proceed to establish the structure of our software solution by modeling the processes of evaluation and remediation of the learner's academic skills.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114727497","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 : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875596
Sawssen Bacha, O. Taouali, N. Liouane
The conception of a Computer-Aided Diagnosis system (CAD) using Artificial Intelligence (AI) is a hot topic in the domain of medical diagnosis. Recently, many approaches have been developed. In the proposed work, a novel classification technique from mammograms based on Kernel Extreme Learning Machine (KELM) and Kernel Partial Least Square (KPLS) method is introduced. The suggested algorithm first used the KPLS algorithm to extract features from the images. The extracted characteristics were then sent to the KELM classifier. In order to improve the generalization of the proposed approach, the cross-validation strategy was used. The simulation results were tested on the Mammographic Image Analysis Society (MIAS) dataset and measured using accuracy, F score, sensitivity, and specificity analysis. These results were compared to existing approaches tested on the same dataset and it was observed that the proposed work is the most efficient.
{"title":"An improved KPLS-KELM method for breast cancer detection","authors":"Sawssen Bacha, O. Taouali, N. Liouane","doi":"10.1109/SETIT54465.2022.9875596","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875596","url":null,"abstract":"The conception of a Computer-Aided Diagnosis system (CAD) using Artificial Intelligence (AI) is a hot topic in the domain of medical diagnosis. Recently, many approaches have been developed. In the proposed work, a novel classification technique from mammograms based on Kernel Extreme Learning Machine (KELM) and Kernel Partial Least Square (KPLS) method is introduced. The suggested algorithm first used the KPLS algorithm to extract features from the images. The extracted characteristics were then sent to the KELM classifier. In order to improve the generalization of the proposed approach, the cross-validation strategy was used. The simulation results were tested on the Mammographic Image Analysis Society (MIAS) dataset and measured using accuracy, F score, sensitivity, and specificity analysis. These results were compared to existing approaches tested on the same dataset and it was observed that the proposed work is the most efficient.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126482689","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 : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875502
H. Dammak, Oumaima Mejri, Meriem Riahi, Faouzi Moussa
Smartphones come pre-loaded with a relatively similar set of applications (abbr. apps) for all users of that particular smartphone brand. They treat users as if they are all part of one big group. This is a simplistic supposition that all smartphone users are alike and have similar usage characteristics. Furthermore, mobile user interfaces are static and do not adapt to the way apps are used. The device maker determines the app icon and app groups on the pre-existing widgets and they stay intact in their current state regardless of the user’s behavior. In this regard, based on app usage behavior, there is a clear need to first identify the groups of user behaviors and then adapt the interface for each user group. In this paper, we propose an ML-based approach to discover users’ group behaviors based on their mobile application usage, with the objective of delivering an appropriate interface adaptation for each user group. To this end, we tested our method on a real dataset that we collected from real users over a one-month period. We discuss in this paper the discovered clusters of users’ behavior and we outline the parties who might benefit from our findings.
{"title":"User Group Profiling through Mobile Application Usage Behavior","authors":"H. Dammak, Oumaima Mejri, Meriem Riahi, Faouzi Moussa","doi":"10.1109/SETIT54465.2022.9875502","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875502","url":null,"abstract":"Smartphones come pre-loaded with a relatively similar set of applications (abbr. apps) for all users of that particular smartphone brand. They treat users as if they are all part of one big group. This is a simplistic supposition that all smartphone users are alike and have similar usage characteristics. Furthermore, mobile user interfaces are static and do not adapt to the way apps are used. The device maker determines the app icon and app groups on the pre-existing widgets and they stay intact in their current state regardless of the user’s behavior. In this regard, based on app usage behavior, there is a clear need to first identify the groups of user behaviors and then adapt the interface for each user group. In this paper, we propose an ML-based approach to discover users’ group behaviors based on their mobile application usage, with the objective of delivering an appropriate interface adaptation for each user group. To this end, we tested our method on a real dataset that we collected from real users over a one-month period. We discuss in this paper the discovered clusters of users’ behavior and we outline the parties who might benefit from our findings.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133979745","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 : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875804
M. Abidi, A. B. Rhouma, J. Belhadj
In this paper, a comparative study of two photovoltaic water pumping architectures is carried out in order to enhance hydraulic efficiency over one year. The first is based on exploiting a powerful motor pump, while the second employs three pumping units to build a multi-pump water station for the same power range. Basing on the architecture nature, the first system is executed by a simple conditional algorithm, while the second is executed using mixed-integer linear programming as an optimal power-sharing strategy to maximize the water pumped volume. Static models of the different motor pumps are extracted from WinCAPS software and simulated using MATLAB. Simulation results show the effectiveness of the second architecture in energetic and water volume viewpoint.
{"title":"Comparative study of mono-pump and multi-pump PV water system and MILP effectiveness in water production improvement","authors":"M. Abidi, A. B. Rhouma, J. Belhadj","doi":"10.1109/SETIT54465.2022.9875804","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875804","url":null,"abstract":"In this paper, a comparative study of two photovoltaic water pumping architectures is carried out in order to enhance hydraulic efficiency over one year. The first is based on exploiting a powerful motor pump, while the second employs three pumping units to build a multi-pump water station for the same power range. Basing on the architecture nature, the first system is executed by a simple conditional algorithm, while the second is executed using mixed-integer linear programming as an optimal power-sharing strategy to maximize the water pumped volume. Static models of the different motor pumps are extracted from WinCAPS software and simulated using MATLAB. Simulation results show the effectiveness of the second architecture in energetic and water volume viewpoint.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128948486","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 : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875503
Amal Hkiri, Mouna Karmani, Mohsen Machhout
Recent years have witnessed impressive advances in technology which led to the rapid growth of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) using numerous low-powered devices with a huge number of actuators and sensors. These devices gather and exchange data over the internet and generate enormous amounts of data needed to be secured. Although traditional cryptography provides an efficient means of addressing device and communication confidentiality, integrity, and authenticity issues, it may not be appropriate for very resource-constrained systems, particularly for end-nodes such as a simply connected sensor. Thus, there is an ascent need to use lightweight cryptography (LWC) providing the needed level of security with less complexity, area and energy overhead. In this paper, four lightweight cryptographic algorithms called PRESENT, LED, Piccolo, and SPARX were implemented over a Contiki-based IoT operating system, dedicated for IoT platforms, and assessed regarding RAM and ROM usage, power and energy consumption, and CPU cycles number. The Cooja network simulator is used in this study to determine the best lightweight algorithms to use in IoT applications utilizing wireless sensor networks technology.
{"title":"Implementation and Performance Analysis of Lightweight Block Ciphers for IoT applications using the Contiki Operating system","authors":"Amal Hkiri, Mouna Karmani, Mohsen Machhout","doi":"10.1109/SETIT54465.2022.9875503","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875503","url":null,"abstract":"Recent years have witnessed impressive advances in technology which led to the rapid growth of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) using numerous low-powered devices with a huge number of actuators and sensors. These devices gather and exchange data over the internet and generate enormous amounts of data needed to be secured. Although traditional cryptography provides an efficient means of addressing device and communication confidentiality, integrity, and authenticity issues, it may not be appropriate for very resource-constrained systems, particularly for end-nodes such as a simply connected sensor. Thus, there is an ascent need to use lightweight cryptography (LWC) providing the needed level of security with less complexity, area and energy overhead. In this paper, four lightweight cryptographic algorithms called PRESENT, LED, Piccolo, and SPARX were implemented over a Contiki-based IoT operating system, dedicated for IoT platforms, and assessed regarding RAM and ROM usage, power and energy consumption, and CPU cycles number. The Cooja network simulator is used in this study to determine the best lightweight algorithms to use in IoT applications utilizing wireless sensor networks technology.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132277538","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 : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875532
Salima Brachemi-Meftah, F. Barigou, Abdelaziz Djendara, Oussama Zaoui
In Algeria, sentiment analysis for Algerian dialect becomes very important for organizations and companies to track customer feedback, to predict their satisfaction, and to assess their opinions over time. However, identification of sentiments is a challenging task; (i) the Algerian dialect is an informal language without rigorous rules of writing and standardization. It is mainly based on Modern Standard Arabic (MSA) vocabulary, where the majority of the original words are modified both phonologically and morphologically. It is also based on a set of foreign words from Turkish, Spanish and French as well Tamazight. This is called code switching. (ii) Another problem which is obviously present in the Algerian dialect is the fact that a word with one form of pronunciation can be written in several forms. Therefore, our objective is to consider these two issues within the process of sentiment analysis of Algerian dialect. To this end, we propose to examine the impact of dimensionality reduction techniques such as lemmatization, stemming, feature selection and in particular our extended Soundex algorithm on the system performance. We used a supervised machine learning approach without going through a translation step into MSA or transliteration into another target language like French. We compare the performance of five classifiers with and without the use of dimensionality techniques. Results show that feature selection combined with multinomial Naive Bayes classifier gives an F1 score of 83.20% and attribute reduction rate of 82.65%.
{"title":"Impact of Dimensionality Reduction on Sentiment Analysis of Algerian Dialect","authors":"Salima Brachemi-Meftah, F. Barigou, Abdelaziz Djendara, Oussama Zaoui","doi":"10.1109/SETIT54465.2022.9875532","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875532","url":null,"abstract":"In Algeria, sentiment analysis for Algerian dialect becomes very important for organizations and companies to track customer feedback, to predict their satisfaction, and to assess their opinions over time. However, identification of sentiments is a challenging task; (i) the Algerian dialect is an informal language without rigorous rules of writing and standardization. It is mainly based on Modern Standard Arabic (MSA) vocabulary, where the majority of the original words are modified both phonologically and morphologically. It is also based on a set of foreign words from Turkish, Spanish and French as well Tamazight. This is called code switching. (ii) Another problem which is obviously present in the Algerian dialect is the fact that a word with one form of pronunciation can be written in several forms. Therefore, our objective is to consider these two issues within the process of sentiment analysis of Algerian dialect. To this end, we propose to examine the impact of dimensionality reduction techniques such as lemmatization, stemming, feature selection and in particular our extended Soundex algorithm on the system performance. We used a supervised machine learning approach without going through a translation step into MSA or transliteration into another target language like French. We compare the performance of five classifiers with and without the use of dimensionality techniques. Results show that feature selection combined with multinomial Naive Bayes classifier gives an F1 score of 83.20% and attribute reduction rate of 82.65%.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134479162","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 : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875746
N. Badri, Leila Nasraoui, L. Saidane
This paper reviews the important application areas of blockchain in Wireless Sensor Networks (WSN) and Internet of Things (IoT) applications. We identify areas where current IoT processes can be enhanced through the use of this new technology with emphasis on the issues addressed in Wireless Body Sensor Networks. This use case is discussed in detail, identifying a suitable blockchain architecture for an industry that is averse to risk, gathering security challenges in this architecture, and providing existing blockchain solutions for these challenges.
{"title":"Blockchain for WSN and IoT Applications","authors":"N. Badri, Leila Nasraoui, L. Saidane","doi":"10.1109/SETIT54465.2022.9875746","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875746","url":null,"abstract":"This paper reviews the important application areas of blockchain in Wireless Sensor Networks (WSN) and Internet of Things (IoT) applications. We identify areas where current IoT processes can be enhanced through the use of this new technology with emphasis on the issues addressed in Wireless Body Sensor Networks. This use case is discussed in detail, identifying a suitable blockchain architecture for an industry that is averse to risk, gathering security challenges in this architecture, and providing existing blockchain solutions for these challenges.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131848125","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 : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875580
J. B. Salem, M. Lakhoua, M. F. Karoui
In recent years, the supervision has marked a great development thanks to the evolution of the computer science. The goals is to optimize the functioning of the systems and to ensure the safety. In fact, implementing effective supervision of industrial systems is becoming increasingly difficult due to the increasing complexity of these systems. Then, effective supervision requires sharp monitoring of the different states of the system and its parameters. In order to properly identify the states to monitor, we use an analysis function it. For our approach, we will use a numerically controlled machine (CNC) tool as a case study system. In this paper, we propose to conduct a supervision by a methodological gait based on a functional analysis using SADT (Structured Analysis Design Technique) method and a Bond graph modeling.
{"title":"Proposal of a Methodology for Modeling and Supervision of Mechatronic Systems","authors":"J. B. Salem, M. Lakhoua, M. F. Karoui","doi":"10.1109/SETIT54465.2022.9875580","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875580","url":null,"abstract":"In recent years, the supervision has marked a great development thanks to the evolution of the computer science. The goals is to optimize the functioning of the systems and to ensure the safety. In fact, implementing effective supervision of industrial systems is becoming increasingly difficult due to the increasing complexity of these systems. Then, effective supervision requires sharp monitoring of the different states of the system and its parameters. In order to properly identify the states to monitor, we use an analysis function it. For our approach, we will use a numerically controlled machine (CNC) tool as a case study system. In this paper, we propose to conduct a supervision by a methodological gait based on a functional analysis using SADT (Structured Analysis Design Technique) method and a Bond graph modeling.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"43 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131873473","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 : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875799
Malha Merah, Z. Aliouat, C. Kara-Mohamed
The clustering technique is an optimal configuration for the Internet of Things (IoT) networks. It offers several benefits, such as energy conservation, latency reduction, and scalability. Meanwhile, energy consumption remains a major concern. In this regard, we introduce a new clustering approach based on the Self-Organizing Map algorithm (SOM), called Energy Efficient SOM (EESOM), conscious of energy consumption with an energy-aware cluster-head (CH) rotation policy that considers the current energy of cluster nodes and their distance from the winning neuron to determine the best CH. The dynamic CH-rotation avoids unbalanced energy consumption for the successive CHs in the cluster and reduces their premature death. When choosing a CH with the minimum distance to the winning neuron, the one with the minimum Euclidean distance to the member nodes will be elected. Consequently, the energy needed by members to send the collected data to their CH is reduced, and the lifetime of the network can be extended. Simulation results indicate that EESOM effectively reduces energy consumption and spreads the network lifespan.
聚类技术是物联网(IoT)网络的最优配置。它提供了几个好处，比如节约能源、减少延迟和可伸缩性。与此同时，能源消耗仍然是一个主要问题。在这方面，我们引入了一种新的基于自组织映射算法(SOM)的聚类方法，称为Energy Efficient SOM (EESOM)，它通过能量感知簇头(CH)旋转策略来意识到能量消耗，该策略考虑了簇节点的当前能量及其与获胜神经元的距离，以确定最佳的CH。动态CH旋转避免了簇中连续CHs的能量消耗不平衡，减少了它们的过早死亡。当选择到获胜神经元距离最小的CH时，将选择到成员节点欧几里德距离最小的CH。因此，成员将收集到的数据发送到他们的CH所需的能量减少了，并且可以延长网络的生命周期。仿真结果表明，EESOM有效地降低了网络能耗，延长了网络寿命。
{"title":"An Energy Efficient Self Organizing Map Based Clustering Protocol For IoT Networks","authors":"Malha Merah, Z. Aliouat, C. Kara-Mohamed","doi":"10.1109/SETIT54465.2022.9875799","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875799","url":null,"abstract":"The clustering technique is an optimal configuration for the Internet of Things (IoT) networks. It offers several benefits, such as energy conservation, latency reduction, and scalability. Meanwhile, energy consumption remains a major concern. In this regard, we introduce a new clustering approach based on the Self-Organizing Map algorithm (SOM), called Energy Efficient SOM (EESOM), conscious of energy consumption with an energy-aware cluster-head (CH) rotation policy that considers the current energy of cluster nodes and their distance from the winning neuron to determine the best CH. The dynamic CH-rotation avoids unbalanced energy consumption for the successive CHs in the cluster and reduces their premature death. When choosing a CH with the minimum distance to the winning neuron, the one with the minimum Euclidean distance to the member nodes will be elected. Consequently, the energy needed by members to send the collected data to their CH is reduced, and the lifetime of the network can be extended. Simulation results indicate that EESOM effectively reduces energy consumption and spreads the network lifespan.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122040613","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 : 2022-05-28DOI: 10.1109/SETIT54465.2022.9875735
Naoufel Ismail, M. Bouaïcha
An accurate method associated with an optimization procedure for studying the current-voltage (I-V) characteristics prediction of solar modules for irradiance and temperature is carried out. The method is based on Artificial Neural Networks (ANN). In the literature, different ANN architectures have been used to translate the solar module I-V curve to any temperature and irradiance conditions. We don’t find in these works an optimization study of the data used in the ANN training. In this work, we describe a new procedure to optimize the temperature and the irradiance values number used in the network training in order to design an ANN model with a few data used in the ANN training and with a high prediction accuracy. In order to validate this procedure, we have compared the I-V curves predicted by ANN with those obtained by simulations using analytical expressions. Results show a prediction accuracy between 99.3% and 99.9%.
{"title":"Artificial Neural Network Based Prediction of the Effect of Temperature and Irradiance on Photovoltaic Current-Voltage Curves","authors":"Naoufel Ismail, M. Bouaïcha","doi":"10.1109/SETIT54465.2022.9875735","DOIUrl":"https://doi.org/10.1109/SETIT54465.2022.9875735","url":null,"abstract":"An accurate method associated with an optimization procedure for studying the current-voltage (I-V) characteristics prediction of solar modules for irradiance and temperature is carried out. The method is based on Artificial Neural Networks (ANN). In the literature, different ANN architectures have been used to translate the solar module I-V curve to any temperature and irradiance conditions. We don’t find in these works an optimization study of the data used in the ANN training. In this work, we describe a new procedure to optimize the temperature and the irradiance values number used in the network training in order to design an ANN model with a few data used in the ANN training and with a high prediction accuracy. In order to validate this procedure, we have compared the I-V curves predicted by ANN with those obtained by simulations using analytical expressions. Results show a prediction accuracy between 99.3% and 99.9%.","PeriodicalId":126155,"journal":{"name":"2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132506492","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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