International journal of hybrid intelligent systems最新文献_第3页

Tuned long short-term memory model for Ethereum price forecasting via an arithmetic optimization algorithm 通过算法优化算法对以太坊价格预测的长短期记忆模型进行了优化

International journal of hybrid intelligent systems Pub Date : 2023-05-06 DOI: 10.3233/his-230003

Luka Jovanovic, I. Strumberger, N. Bačanin, M. Zivkovic, Milos Antonijevic, Peter Bisevac

{"title":"Tuned long short-term memory model for Ethereum price forecasting via an arithmetic optimization algorithm","authors":"Luka Jovanovic, I. Strumberger, N. Bačanin, M. Zivkovic, Milos Antonijevic, Peter Bisevac","doi":"10.3233/his-230003","DOIUrl":"https://doi.org/10.3233/his-230003","url":null,"abstract":"Machine learning as a subset of artificial intelligence presents a promising set of algorithms for tackling increasingly complex challenges. A notable ability of this subgroup of algorithms to tackle tasks without explicit programming coupled with the expanding availability of computational resources and information transparency has made it possible to utilize algorithms to forecast prices. In recent years, cryptocurrency has increased in popularity and has seen wider adoption as a payment method. Cryptocurrency trading and mining have become a potentially very lucrative venture. However, due to the instability of cryptocurrency prices, casting accurate predictions can be quite challenging. A novel way of approaching this challenge is by tackling it through time-series forecasting. A particularly promising method for tackling this type of problem is through the utilization of long-short-term memory artificial neural networks to attain accurate prediction results. However, the forecasting accuracy of machine learning models is highly dependent on adequate hyperparameter settings. Thus, this work presents an improved variation of the arithmetic optimization algorithm, tasked with selecting the best values of a long-short term neural network casting price predictions. The presented approach has been evaluated on publicly available real-world Ethereum trading price data. The attained results of a comparative analysis against several popular metaheuristics indicate that the presented method achieved excellent results, and outperformed aforementioned algorithms in one and four-step ahead predictions.","PeriodicalId":88526,"journal":{"name":"International journal of hybrid intelligent systems","volume":"19 1","pages":"27-43"},"PeriodicalIF":0.0,"publicationDate":"2023-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83757845","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

Bayesian model selection for barriers in online learning behaviors 在线学习行为障碍的贝叶斯模型选择

International journal of hybrid intelligent systems Pub Date : 2023-05-06 DOI: 10.3233/his-230001

B. Khoi

引用次数: 0

Comparative study of Moroccan stock price prediction with trend technical indicators 趋势技术指标预测摩洛哥股票价格的比较研究

International journal of hybrid intelligent systems Pub Date : 2023-05-06 DOI: 10.3233/his-230002

Abdelhadi Ifleh, Azdine Bilal, Mounime El Kabbouri

引用次数: 0

Hybrid optimisation and machine learning models for wind and solar data prediction 风能和太阳能数据预测的混合优化和机器学习模型

International journal of hybrid intelligent systems Pub Date : 2023-05-06 DOI: 10.3233/his-230004

Yahia Amoura, Santiago Torres, J. Lima, Ana I. Pereira

引用次数: 0

Hybrid Intelligent Systems: 22nd International Conference on Hybrid Intelligent Systems (HIS 2022), December 13–15, 2022 混合智能系统:第22届混合智能系统国际会议(HIS 2022)， 2022年12月13日至15日

International journal of hybrid intelligent systems Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-27409-1

引用次数: 0

An hybrid cluster-based data centric routing protocol assisted by mobile sink for IoT system 一种基于混合集群的移动sink辅助物联网系统数据中心路由协议

International journal of hybrid intelligent systems Pub Date : 2022-10-08 DOI: 10.3233/his-220012

Omnia Mezghani, Mahmoud Mezghani

{"title":"An hybrid cluster-based data centric routing protocol assisted by mobile sink for IoT system","authors":"Omnia Mezghani, Mahmoud Mezghani","doi":"10.3233/his-220012","DOIUrl":"https://doi.org/10.3233/his-220012","url":null,"abstract":"Nowadays, using mobile computing devices and the Internet of Things (IoT) in networks have posed several challenges to match up the forthcoming technological requirements. Wireless Sensors Network (WSN) is considered as an important component of the IoT which produces a massive amount of data (big data). However, dealing with limited capacities of the elementary components of a network in an IoT enabled WSN, is a key challenge. The existing approaches in the literature are inadequate for large networks and cannot be applied to IoT platform without adaptation. Data Centric Network (DCN) is an important notion for the future Internet architecture to resolve the problems related to big data manipulation. In fact, using a DCN strategy for the resource limited capacities WSN enabled IoT networks is beneficial to manage densely deployed and mobile components to enhance the data gathering mechanism. In this context, this paper proposes an IoT cluster based routing protocol for data centric mobile wireless sensors networks named ICMWSN. The proposed algorithm fits with a WSN belonging a large number of mobile sensors as well as a mobile sink. It is based on a clustering technique to form multi-hops clusters around fixed pre-elected CHs. Besides, an effective tour construction method is involved for the mobile sink to collect data from the eventual cluster heads. The extensive simulation results proved that ICMWSN outperformed the compared methods in terms of energy consumption, network lifetime and data delivery rate.","PeriodicalId":88526,"journal":{"name":"International journal of hybrid intelligent systems","volume":"146 1","pages":"137-148"},"PeriodicalIF":0.0,"publicationDate":"2022-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76573168","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 bi-objective model for territorial design 地域设计的双目标模型

International journal of hybrid intelligent systems Pub Date : 2022-09-16 DOI: 10.3233/his-220011

María Beatríz Bernábe Loranca, Carlos Guillén Galván, Rogelio González Velázquez, Gerardo Martínez Guzman, Alberto José Luís Carrillo Canán

{"title":"A bi-objective model for territorial design","authors":"María Beatríz Bernábe Loranca, Carlos Guillén Galván, Rogelio González Velázquez, Gerardo Martínez Guzman, Alberto José Luís Carrillo Canán","doi":"10.3233/his-220011","DOIUrl":"https://doi.org/10.3233/his-220011","url":null,"abstract":"The clustering of spatial-geographic units, zones or areas has been used to solve problems related to Territorial Design. Clustering adapts to the definition of territorial design for a specific problem, which demands spatial data processing under clustering schemes with topological requirements for the zones. For small sized instances, once the geographical compactness is attended to as an objective function, this problem has been solved by exact methods with an acceptable response time. However, for larger instances and due to the combinatory nature of this problem, the computational complexity increases and the use of approximated methods becomes a necessity, in such a way that when geographical compactness was the only cost function a couple of approximated methods were incorporated giving satisfactory results. A particular case of this kind of problems that has had our attention in recent years is the classification by partitioning of AGEBs (Basic Geographical Units by its initials in Spanish). Some work has been made related to the formation of compact groups of AGEBs, but additional re-strictions were often not considered. A very interesting and highly demanded application problem is to extend the compact clustering to form groups with for some of its descriptive variables. This problem translates to a multi-objective approach that has to pursue two objectives to attain a balance between them. At this point, to reach a set of non-dominated and non-comparable solutions, a method has been included that allows obtaining the Pareto front through the Hasse diagram, which implies proposing a mathematical programming model and the synthetic resulting between compactness and homogeneity.","PeriodicalId":88526,"journal":{"name":"International journal of hybrid intelligent systems","volume":"10 1","pages":"149-160"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89535751","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

Soft computing and image processing techniques for COVID-19 prediction in lung CT scan images 肺部CT扫描图像中COVID-19预测的软计算和图像处理技术

International journal of hybrid intelligent systems Pub Date : 2022-05-16 DOI: 10.3233/his-220009

Neeraj Venkatasai L. Appari, Mahendra G. Kanojia

{"title":"Soft computing and image processing techniques for COVID-19 prediction in lung CT scan images","authors":"Neeraj Venkatasai L. Appari, Mahendra G. Kanojia","doi":"10.3233/his-220009","DOIUrl":"https://doi.org/10.3233/his-220009","url":null,"abstract":"COVID-19 is a contagious respiratory illness that can be passed from person to person. Because it affects the lungs, damages blood arteries, and causes cardiac problems, COVID-19 must be diagnosed quickly. The reverse transcriptase polymerase chain reaction (RT-PCR) is a method for detecting COVID-19, but it is time consuming and labor expensive, as well as putting the person collecting the sample in danger. As a result, clinicians prefer to use CT scan and Xray images. COVID-19 classification can be done manually, however AI makes the process go faster. AI approaches include image processing, machine learning, and deep learning. An AI model is required to diagnose COVID-19, and a dataset is necessary to train that model. A dataset consists of the information from which the model is trained. This paper consists of the review of different image processing, machine learning and deep learning papers proposed by different researchers. As well as models based on deep learning and pretrained model using gradient boosting algorithm The goal of this paper is to provide information for future researchers to work with.","PeriodicalId":88526,"journal":{"name":"International journal of hybrid intelligent systems","volume":"47 1","pages":"111-131"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84135185","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

Cost-forced and repeated selective information minimization and maximization for multi-layered neural networks 多层神经网络的代价强制和重复选择信息最小化和最大化

International journal of hybrid intelligent systems Pub Date : 2022-04-28 DOI: 10.3233/his-220008

R. Kamimura

{"title":"Cost-forced and repeated selective information minimization and maximization for multi-layered neural networks","authors":"R. Kamimura","doi":"10.3233/his-220008","DOIUrl":"https://doi.org/10.3233/his-220008","url":null,"abstract":"The present paper aims to propose a new information-theoretic method to minimize and maximize selective information repeatedly. In particular, we try to solve the incomplete information control problem, where information cannot be fully controlled due to the existence of many contradictory factors inside. For this problem, the cost in terms of the sum of absolute connection weights is introduced for neural networks to increase and decrease information against contradictory forces in learning, such as error minimization. Thus, this method is called a “cost-forced” approach to control information. The method is contrary to the conventional regularization approach, where the cost has been used passively or negatively. The present method tries to use the cost positively, meaning that the cost can be augmented if necessary. The method was applied to an artificial and symmetric data set. In the symmetric data set, we tried to show that the symmetric property of the data set could be obtained by appropriately controlling information. In the second data set, that of residents in a nursing home, obtained by the complicated procedures of natural language processing, the experimental results confirmed that the present method could control selective information to extract non-linear relations as well as linear ones in increasing interpretation and generalization performance.","PeriodicalId":88526,"journal":{"name":"International journal of hybrid intelligent systems","volume":"1 1","pages":"69-95"},"PeriodicalIF":0.0,"publicationDate":"2022-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88621457","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

Federated learning: Applications, challenges and future directions 联邦学习:应用、挑战和未来方向

International journal of hybrid intelligent systems Pub Date : 2022-04-21 DOI: 10.3233/HIS-220006

Subrato Bharati, M. Mondal, Prajoy Podder, V. Prasath

{"title":"Federated learning: Applications, challenges and future directions","authors":"Subrato Bharati, M. Mondal, Prajoy Podder, V. Prasath","doi":"10.3233/HIS-220006","DOIUrl":"https://doi.org/10.3233/HIS-220006","url":null,"abstract":"Federated learning (FL) refers to a system in which a central aggregator coordinates the efforts of several clients to solve the issues of machine learning. This setting allows the training data to be dispersed in order to protect the privacy of each device. This paper provides an overview of federated learning systems, with a focus on healthcare. FL is reviewed in terms of its frameworks, architectures and applications. It is shown here that FL solves the preceding issues with a shared global deep learning (DL) model via a central aggregator server. Inspired by the rapid growth of FL research, this paper examines recent developments and provides a comprehensive list of unresolved issues. Several privacy methods including secure multiparty computation, homomorphic encryption, differential privacy and stochastic gradient descent are described in the context of FL. Moreover, a review is provided for different classes of FL such as horizontal and vertical FL and federated transfer learning. FL has applications in wireless communication, service recommendation, intelligent medical diagnosis system and healthcare, which we review in this paper. We also present a comprehensive review of existing FL challenges for example privacy protection, communication cost, systems heterogeneity, unreliable model upload, followed by future research directions.","PeriodicalId":88526,"journal":{"name":"International journal of hybrid intelligent systems","volume":"72 1","pages":"19-35"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74788201","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: 16