2014 14th UK Workshop on Computational Intelligence (UKCI)最新文献_第2页

Evolution-in-materio: Solving function optimization problems using materials 材料进化:利用材料解决功能优化问题

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930152

Maktuba Mohid, J. Miller, Simon Harding, G. Tufte, O. R. Lykkebø, M. K. Massey, M. Petty

引用次数: 20

Integration strategies for toxicity data from an empirical perspective 从实证角度看毒性数据的整合策略

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930153

Longzhi Yang, D. Neagu

{"title":"Integration strategies for toxicity data from an empirical perspective","authors":"Longzhi Yang, D. Neagu","doi":"10.1109/UKCI.2014.6930153","DOIUrl":"https://doi.org/10.1109/UKCI.2014.6930153","url":null,"abstract":"The recent development of information techniques, especially the state-of-the-art “big data” solutions, enables the extracting, gathering, and processing large amount of toxicity information from multiple sources. Facilitated by this technology advance, a framework named integrated testing strategies (ITS) has been proposed in the predictive toxicology domain, in an effort to intelligently jointly use multiple heterogeneous toxicity data records (through data fusion, grouping, interpolation/extrapolation etc.) for toxicity assessment. This will ultimately contribute to accelerating the development cycle of chemical products, reducing animal use, and decreasing development costs. Most of the current study in ITS is based on a group of consensus processes, termed weight of evidence (WoE), which quantitatively integrate all the relevant data instances towards the same endpoint into an integrated decision supported by data quality. Several WoE implementations for the particular case of toxicity data fusion have been presented in the literature, which are collectively studied in this paper. Noting that these uncertainty handling methodologies are usually not simply developed from conventional probability theory due to the unavailability of big datasets, this paper first investigates the mathematical foundations of these approaches. Then, the investigated data integration models are applied to a representative case in the predictive toxicology domain, with the experimental results compared and analysed.","PeriodicalId":315044,"journal":{"name":"2014 14th UK Workshop on Computational Intelligence (UKCI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124737528","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

A novel approach for ANFIS modelling based on Grey system theory for thermal error compensation 基于灰色系统理论的热误差补偿ANFIS建模新方法

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930155

Ali M. Abdulshahed, A. Longstaff, S. Fletcher

引用次数: 9

Prediction of driver fatigue: Approaches and open challenges 驾驶员疲劳预测:方法和公开挑战

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930193

Hilal Abbood, W. Al-Nuaimy, Ali Al-Ataby, Sameh A. Salem, Hamzah S. AlZu'bi

{"title":"Prediction of driver fatigue: Approaches and open challenges","authors":"Hilal Abbood, W. Al-Nuaimy, Ali Al-Ataby, Sameh A. Salem, Hamzah S. AlZu'bi","doi":"10.1109/UKCI.2014.6930193","DOIUrl":"https://doi.org/10.1109/UKCI.2014.6930193","url":null,"abstract":"Fatigue is a mental process that grows gradually and affects human reaction time and the consciousness. It is one of the causes of road fatal accidents around the globe. Although it is now generally accepted that fatigue plays an important role in road safety, it is still largely left to individual drivers to manage. The recent research in this area focuses on fatigue detection and the existing systems alert the drivers in severe fatigued stage. These systems use either physiological signs of the fatigue or the behavioural reaction to generate alerts. This research investigates the feasibility of using a group of fatigue symptoms (such as pupil response, gaze patterns, steering reaction and EEG) to build a robust fatigue detection algorithm that can be used in a real-life system for the early prediction and avoidance of fatigue development. Intensive testing and validation stages are required to ensure the reliability and the suitability of the system that should be able to detect fatigue levels at different degrees of tiredness. Moreover, the proposed system predicts subsequent stages of fatigue and generates an approximate behavioural model for each individual driver to enable more personalised and effective intervention.","PeriodicalId":315044,"journal":{"name":"2014 14th UK Workshop on Computational Intelligence (UKCI)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132452583","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: 23

A benchmark generator for dynamic multi-objective optimization problems 动态多目标优化问题的基准生成器

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930171

Shouyong Jiang, Shengxiang Yang

引用次数: 12

Integrate classifier diversity evaluation to feature selection based classifier ensemble reduction 将分类器多样性评价与基于特征选择的分类器集成约简相结合

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930156

Gang Yao, F. Chao, Hualin Zeng, Minghui Shi, Min Jiang, Changle Zhou

引用次数: 8

PermGA algorithm for a sequential optimal space filling DoE framework 基于PermGA算法的顺序最优空间填充DoE框架

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930172

M. R. Kianifar, F. Campean, A. Wood

引用次数: 7

Pathfinding in partially explored games environments: The application of the A∗ Algorithm with occupancy grids in Unity3D 部分探索游戏环境中的寻路:A *算法在Unity3D中占有网格的应用

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930151

J. Stamford, Arjab Singh Khuman, Jenny Carter, S. Ahmadi

引用次数: 9

Hybridisation of decomposition and GRASP for combinatorial multiobjective optimisation 组合多目标优化中分解与抓取的混合

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930173

Ahmad Alhindi, Qingfu Zhang, E. Tsang

引用次数: 9

Modeling neural plasticity in echo state networks for time series prediction 时间序列预测中回声状态网络的神经可塑性建模

2014 14th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2014-10-20 DOI: 10.1109/UKCI.2014.6930163

Mohd-Hanif Yusoff, Yaochu Jin

引用次数: 4