2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI)最新文献

Ensembling Routing Algorithms 集成路由算法

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118832

Zhen-qiang Wu, R. Falcon, V. Groza, E. Petriu

{"title":"Ensembling Routing Algorithms","authors":"Zhen-qiang Wu, R. Falcon, V. Groza, E. Petriu","doi":"10.1109/SACI49304.2020.9118832","DOIUrl":"https://doi.org/10.1109/SACI49304.2020.9118832","url":null,"abstract":"Energy and time consumption are the two most common challenges regarding communication optimization in the Wireless sensor network (WSN) routing algorithms. There are many different approaches for solving these two major issues in WSNs. These approaches optimize over time or energy separately and yet rarely take into account multiple criteria when choosing the next hop on the route. In order to address this open problem in WSNs, it is advantageous to combine multiple criteria during the next hop selection step. In this paper, we propose a new concept called Routing Ensembles. Our approach takes into account the individual selection criterion for the next hop using various multiple routing algorithms and applies a voting mechanism to decide on the next hop in the route collectively. We tested our routing ensemble with five well-known base routing methods, i.e., Greedy, NFP, MPoPR, MFR, and Compass and then selected the most voted node as the next hop. This process repeats until either the destination node is reached or the routing process fails. This concept was tested and validated using multiple simulated networks of varying sizes. The experimental analysis concluded that the routing ensembles allowed us to: (1) increase the delivery rate regardless of the network field size, (2) minimize both the energy and time consumption and (3) enhance the network performance only using traditional and directly routing algorithms.","PeriodicalId":110307,"journal":{"name":"2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"48 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116947559","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

Investigation of the Fill Factors for a DSSC Solar Cell on the Basis of Module Temperature Using Different Artificial Irradiations 基于组件温度的DSSC太阳能电池在不同人工辐照下的填充系数研究

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118828

Ervin Rácz, Z. Varga

引用次数: 2

Using self-organizing maps as unsupervised learning models for meteorological data mining 利用自组织地图作为气象数据挖掘的无监督学习模型

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118821

A. Mihai

引用次数: 1

Analysing protein dynamics using machine learning based generative models 使用基于机器学习的生成模型分析蛋白质动力学

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118834

Alexandra-Ioana Albu, G. Czibula

引用次数: 2

Modelling of accidents for four lane non-urban highways using artificial neural networks technique 基于人工神经网络技术的四车道非城市公路交通事故建模

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118819

Anteneh Afework, T. Sipos

{"title":"Modelling of accidents for four lane non-urban highways using artificial neural networks technique","authors":"Anteneh Afework, T. Sipos","doi":"10.1109/SACI49304.2020.9118819","DOIUrl":"https://doi.org/10.1109/SACI49304.2020.9118819","url":null,"abstract":"the purpose of road accidents forecasting is to analyze the tendency of road accidents under existing road traffic conditions, evaluate the feasibility and practical effectiveness of traffic safety measures reasonably, control the factors affecting road accidents, and reduce the traffic accidents. The characteristics such as non-linearity, randomness and uncertainty in traffic system make it difficult to forecast road accidents, the behavioral feature of traffic system. The objectives of this study are to determine the critical accident variables for accident prediction purposes, to utilize Artificial Neural Network (ANN) as a tool for accident prediction analysis, and to develop an Accident Prediction Model. This study uses a series of artificial neural networks to model and estimate accident by the applied software that is NeuroSolutions 6.0. An important implication of this paper after sensitivity analysis is that the variables like mixed-use developments, side-drain condition, guard rail, marker-post, chevron markings and curve warnings, cross-drainage works, over-head structures, Fly-over Bridge, side roads/access roads, under-pass, and volume of traffic are most significant factors which increase accident.","PeriodicalId":110307,"journal":{"name":"2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132529991","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: 4

The Differences in Hydration and Dehydration Status: Physiological Characteristics in Students 水合脱水状态的差异:学生的生理特征

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118843

Ogbolu Melvin Omone, L. Kovács, M. Kozlovszky

引用次数: 1

ASTERICS: Projection-based Classification of EEG with Asymmetric Loss Linear Regression and Genetic Algorithm 基于非对称损失线性回归和遗传算法的脑电投影分类

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118837

Krisztián Búza

引用次数: 2

Deductive Synthesis of Min-Max-Sort Using Multisets in Theorema 定理中使用多集的最小-最大排序的演绎综合

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118814

I. Dramnesc, T. Jebelean

{"title":"Deductive Synthesis of Min-Max-Sort Using Multisets in Theorema","authors":"I. Dramnesc, T. Jebelean","doi":"10.1109/SACI49304.2020.9118814","DOIUrl":"https://doi.org/10.1109/SACI49304.2020.9118814","url":null,"abstract":"We demonstrate the deductive synthesis of the Min-Max-Sort algorithm using multisets in the frame of the Theorema system. Starting from the logical specification of the sorting function (input and output conditions), we show how to construct a synthesis conjecture, from whose proof the algorithm can be constructed. For the proof we choose those inference methods and induction principles such that the synthesized algorithm consists of selecting at each step the minimum and the maximum of the list, and moving them at the ends of the list. We also show how to add, on a logical basis, a specific flag in order to stop the recursion as soon as the list is already sorted. During the main proof new conjectures are produced for the synthesis of auxiliary algorithms, and this process repeats in a cascading fashion until all necessary algorithms are produced. Our proof techniques, which are in natural style, include a novel approach using multisets and the use of cover sets for realizing Noetherian induction. The later has the advantage that the concrete induction hypotheses are created dynamically during the proof of the corresponding induction conclusion, thus no concrete induction principle or algorithm scheme is needed in advance. The synthesis mechanism is implemented in the frame of the Theorema system which allows the construction of mathematical theories, proving in natural style, and computing with the synthesized algorithms.","PeriodicalId":110307,"journal":{"name":"2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125786635","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

Examining the Efficiency of Magnetometers in Movement Classification Systems 检验磁力计在运动分类系统中的效率

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118808

Peter Sarcevic

引用次数: 2

Mathematical Formalism of Sequential Automaton with Parallel Branches used in Industrial Automation 工业自动化中具有并行分支的顺序自动机的数学形式

2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2020-05-01 DOI: 10.1109/SACI49304.2020.9118825

D. Ungureanu-Anghel, R. Robu, O. Proștean

引用次数: 1