Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications最新文献_第4页

A Novel Interpretable Model for Solar Radiation Prediction based on Adaptive Fuzzy Clustering and Linguistic Hedges 基于自适应模糊聚类和语言模糊限制的太阳辐射可解释预测模型

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419807

Khalid Bahani, Hamza Ali-Ou-Salah, Mohammed Moujabbir, B. Oukarfi, M. Ramdani

{"title":"A Novel Interpretable Model for Solar Radiation Prediction based on Adaptive Fuzzy Clustering and Linguistic Hedges","authors":"Khalid Bahani, Hamza Ali-Ou-Salah, Mohammed Moujabbir, B. Oukarfi, M. Ramdani","doi":"10.1145/3419604.3419807","DOIUrl":"https://doi.org/10.1145/3419604.3419807","url":null,"abstract":"The designs of solar energy systems depend mainly on the solar radiation that reaches the earth's surface, as it is difficult to determine the amount of solar radiation precisely due to several climatic, geographical and temporal factors. Therefore, forecasting of solar radiation is necessary before using solar energy systems. In this paper, the researchers present an accuracy MAMDANI fuzzy inference system for solar radiation prediction with meteorological data. This system is based with a two-stage method for Fuzzy Rules Learning through Clustering (FRLC). In the first stage, the subtractive clustering is used to extract the fuzzy rules, the second stage is a linguistic approximation and a refinement of the learned solutions with linguistic hedges. FRLC is compared to multilayer feed-forward neural network and support vector regression. The results of the experiments show the efficacy of linguistic fuzzy rules in the forecasting of solar radiation. In parallel with the prediction, the model provides a good balance between interpretability and accuracy.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121887934","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

Tunable Monopole Antenna in the Sub-6 GHz Spectrum for Picocell Base Stations 用于皮cell基站的6ghz以下频谱的可调谐单极天线

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419756

Aicha bembarka, A. Tribak, Hamza Nachouane, L. Setti

引用次数: 0

Identifying Software Cost Attributes of Software Project Management in Global Software Development: An Integrative Framework 全球软件开发中软件项目管理的软件成本属性识别:一个集成框架

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419780

Manal El Bajta, A. Idri

引用次数: 2

Comparison of MCDM Methods for Multi-echelon Inventory System Selection Problem 多级库存系统选择问题的MCDM方法比较

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419783

Nouçaiba Sbai, L. Benabbou, A. Berrado

{"title":"Comparison of MCDM Methods for Multi-echelon Inventory System Selection Problem","authors":"Nouçaiba Sbai, L. Benabbou, A. Berrado","doi":"10.1145/3419604.3419783","DOIUrl":"https://doi.org/10.1145/3419604.3419783","url":null,"abstract":"Nowadays, Multi Criteria Decision Making (MCDM) methods are becoming increasingly used in solving supply chain management problems due to the conflicting criteria involved in this area. In fact, Multi Criteria Decision Making methods help Decision Makers (DMs) deal with the evaluation of multiple alternatives with taking into account their preferences expressed as numerous criteria. Controlling stocks in multi-echelon inventory systems presents many challenges due to the complexity of the supply chains and the inter-dependencies between their nodes. In particular, choosing a multi-echelon inventory policy to send a batch from an installation to another may depend to the inventory status at all sites, which make this decision difficult to take. Most of the time, the Decision Maker seems to be looking for fitting the decision problem to the MCDM method framework and not adjusting the method to the problem situation. We aim in this paper to guide DMs choose the appropriate MCDM method that will aid them select the best multi-echelon inventory policies to adopt for their supply chains. A comparison of different MCDM methods with the use of a set of evaluation criteria will be established in this research work. We intend to provide a framework for comparing multiple MCDM methods for the multi-echelon inventory system selection problem.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131898381","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

Language representation learning models: A comparative study 语言表征学习模式的比较研究

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419773

Sanae Achsas, E. Nfaoui

引用次数: 2

Construction of an accurate automatic lexicon for Arabic sentiment analysis 构建精确的阿拉伯语情感分析自动词典

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419627

Ibtissam Touahri, A. Mazroui

引用次数: 0

The hybrid recommendation of digital educational resources in a distance learning environment: the case of MOOC 远程教育环境下数字教育资源的混合推荐:以MOOC为例

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419621

Hamid Slimani, Oussama Hamal, N. E. Faddouli, S. Bennani, Naila Amrous

{"title":"The hybrid recommendation of digital educational resources in a distance learning environment: the case of MOOC","authors":"Hamid Slimani, Oussama Hamal, N. E. Faddouli, S. Bennani, Naila Amrous","doi":"10.1145/3419604.3419621","DOIUrl":"https://doi.org/10.1145/3419604.3419621","url":null,"abstract":"The accompaniment and the follow-up of the learners in an online training aim at helping the learner to carry out his or her training and to guarantee an adapted and quality learning. During a learning process, personalized search and recommendation of digital educational resources form aspects of this accompaniment. This article presents a search engine and a hybrid recommendation of digital educational resources. This engine allows for filtering and personalized search by providing adapted resources to the users' profiles on the one hand; on the other hand, to making a combination of the collaborative, the content-based and the semantic filtering to propose other additional resources. The semantic filtering is based on the exploitation of SPARQL queries from the system that we propose. They are executed on a remote server containing reusable vocabularies and formalized according to the linked data principles and technologies, such as the Lod Cloud. The result obtained is a set of linked terms to the keywords specified in the search query. These terms are then used to extend the search. We used a search test-set by keywords entered via a form and then we manually analyzed the linked terms obtained and the documents returned. The results obtained by our approach are satisfactory.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129541937","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

K-means, HAC and FCM Which Clustering Approach for Arabic Text? K-means、HAC和FCM哪种聚类方法适合阿拉伯文本?

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419779

Lahbib Ajallouda, F. Z. Fagroud, A. Zellou, E. Benlahmar

引用次数: 1

Online Adaptive Learning: A Review of Literature 在线适应性学习:文献综述

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419759

Jallal Talaghzi, Abdellah Bennane, M. Himmi, M. Bellafkih, Aziza Benomar

引用次数: 37

Recommender E-Learning platform using sentiment analysis aggregation 推荐使用情感分析聚合的电子学习平台

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419784

Jamal Mawane, A. Naji, M. Ramdani

{"title":"Recommender E-Learning platform using sentiment analysis aggregation","authors":"Jamal Mawane, A. Naji, M. Ramdani","doi":"10.1145/3419604.3419784","DOIUrl":"https://doi.org/10.1145/3419604.3419784","url":null,"abstract":"The ubiquity and the fast growth of online resources has made it more and more difficult to try to respect the differences between learners in terms of cognitive ability and knowledge structure. This is even clearer with recommendation algorithms that use traditional collaborative filtering as they struggle through identifying more helpful, user friendly and easy learning resources. On top of that, the incoherent recommended content and the compound and nonlinear data on online learning users cannot be effectively handled, thus making the recommendations less efficient. To increase the level of efficiency of learning resource recommendations, this paper introduces a two steps efficient resource recommendation model. this model is based on unsupervised deep learning machine to identify learning styles and users' clusters, and a sentiment analyzer bonus system, based on user experience, to improve or decrease recommender items list classification. The model integrates also teachers to incite them to enhance the quality and the success rate of appropriate selected items. The elaboration of such a model requires the use of a considerable quantity of data learners' features, course content and assessment attributes. Furthermore, this model needs to incorporate learner interactions features. These are the requirements to build Learner features vector as input for the first step and Learner-Content ratings vector to choose the more efficient learning resource to recommend.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123427043","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