会议信息

LA-CCI 2018: IEEE Latin American Conference on Computational Intelligence

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截稿日期:
2018-06-04 已截稿
通知日期:
2018-07-02
会议日期:
2018-11-07
会议地点:
Guadalajara, Mexico
届数:
5
浏览: 14689   关注: 0   参加: 0
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41.7 / 100
全站第 4,736 名 / 共 5,771 个会议 · 前 83%

人工智能与机器学习 第 616 / 755

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
48
社区关注 (10%)
8
资料公开度 (15%)
25

用到的输入: 有据可查的届次：5 · 过去 24 个月打开过本页的研究者：2 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.2 · 算于 2026-11-09

征稿

LA-CCI 2018 (IEEE Latin American Conference on Computational Intelligence) is an academic conference held in Guadalajara, Mexico on 2018-11-07. The paper submission deadline is 2018-06-04 (extended). Acceptance notifications are sent on 2018-07-02.

Any topic related to Computational Intelligence, mainly but not limited to the following: Problems Single List for all tracks: – Foundations of Computational Intelligence; – Analysis & Identification; – Modeling & Design; – Representation & Interfacing; – Methods & techniques of CI Hybridization; – Simulation & Estimation; – Signal & Sensor Processing; – Machine learning and pattern recognition; – Time series forecasting; – Classification & Clustering; – Search & Optimization (combinatorial, stochastic, dynamic, multimodal, multi-objective, etc); – Constraint handling (Routing, Scheduling, Timetabling, allocation Neighboring, Placement, etc); – Information retrieval & Ambient intelligence – Decision Problems; – Cognitive Robotics; – Image Processing & Computer Vision; – Bio & Medical Informatics – Computational biology; – Information & Network security; – Data & Web Mining; – E-commerce, E-Procurement & E-Government; – Telecommunications and Networking; – Energy generation and energy dispatch; – Parallelization & Hardware Implementations. Approaches (1) Evolutionary & Swarm Computation: – Evolutionary computation; – Swarm intelligence; – Artificial immune systems; – Novel metaheuristics and hyperheuristics; – Memetic and Collective intelligence; – Nature and Bio-inspired methods; – Artificial life. (2) Neural & Learning Systems: – Machine learning; – Neural Computation (+Weightless Systems); – Complex systems; – Wavelets; – Molecular and quantum computing; – Brain-machine interfaces; – Network Sciences; – Local search methods. (3) Fuzzy & Stochastic Modeling: – Fuzzy logic; – Fuzzy optimization and design; – Fuzzy pattern recognition; – Fuzzy control & decision making/support; – Rough sets; – Uncertainty analysis; – Fractals; – Game theory; – Social Simulation; – Multi-agent systems; – Symbolic Systems; – Grey systems. Technologies (1) Evolutionary & Swarm Computation: – Ant colony optimization; – Particle swarm optimization; – Fish School Search; – Bee colony optimization; – Genetic programming and Genetic algorithms; – Cultural Algorithms and Co-Evolution; – Evolutionary Strategy and Differential Evolution; – Evolutionary design & scheduling; – Danger theory and network immune systems; – Firefly optimization; – Glowsworm Swarm Optimization; – Cuckoo search; – Herd optimization; etc. (2) Neural & Learning Systems: – Cognitive systems and applications; – Computer vision; – Hardware Implementations; – Web intelligence; – Natural language processing & Speech understanding; – Supervised and Unsupervised Learning; – Semi-supervised and Weakly Supervised Learning; – Support vector machines; – Local Search Methods (Tabu search, iterated search, etc.) – Reinforcement Learning – Neuroscience and biologically inspired control; – Distributed intelligent systems; etc. (3) Fuzzy & Stochastic Modeling: – Fuzzy sets & Type-2 fuzzy logic; – Approximate reasoning; – Rough sets & data analysis; – Case-Based Reasoning; – Expert systems; – Knowledge engineering. – Adaptive Dynamic Programing & Control; – Convergence and performance analysis; – Bayesian methods; – Monte-Carlo methods and variations; – Markov decision processes; and, – Other Statistical learning.
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