| 1. | Video image segmentation based on bayesian learning
基于贝叶斯学习的视频图像分割 |
| 2. | A bayesian learning based on multi - issues negotiation
基于多议题协商的贝叶斯学习 |
| 3. | A bayesian learning algorithm based on search - coding method
基于搜索编码的简单贝叶斯分类方法 |
| 4. | Relevance vector machine based on bayesian learning and its application in soft sensing
在对带软时间窗车辆调度问题 |
| 5. | Bayesian learning and inference algorithm based on bayesian networks toolbox
基于贝叶斯网络工具箱的贝叶斯学习和推理 |
| 6. | In this essay we focus on the choosing of suitable prior in bayesian learning first of a1l
本论文讨论贝叶斯学习中的一个基本问题?相容性问题 |
| 7. | In continuous - lime framework , assuming that asset price follows stochastic diffusion process , it introduces parametric uncertainty , and applies stochastic dynamic programming to derive the closed - form solution of optimal portfolio choice , which maximizes the expected power utility of investor ' s terminal wealth ; in discrete - time framework , continuous compounding monthly returns of risky asset are assumed to be normal i . 1 . d . , it applies the rule of bayesian learning to do empirical study about two different sample of shanghai exchange composite index
在连续时间下假设资产的价格服从随机扩散过程，引入参数不确定性，利用随机动态规划方法推导出风险资产最优配置的封闭解，使投资者的终期财富期望幂效用最大；在离散时间下假设风险资产的连续复合月收益率服从独立同分布的正态分布，通过贝叶斯学习准则，以上证综合指数不同区间段的两个样本做实证研究。 |
| 8. | Within the framework of sparse bayesian learning , the algorithm extends the relevance vector machine by combining global and local kernels adaptively in the form of multiple kernels , and the improved locality preserving projection ( llp ) is then applied to reduce the column dimension of the multiple kernel input matrix to achieve less training time
在稀疏贝叶斯学习的框架下，该算法首先以多核形式自适应结合全局核函数和局部核函数扩展相关向量机，然后应用改进的保局投影来约简多核输入矩阵的列维数以减少训练时间。 |
| 9. | This research addressed an urban traffic intelligent control system , which adopts a multi - agents coordination in urban traffic control to coordinate the signal of adjacent intersections for eliminating the congestion of traffic network . an agent represents a signal intersection control , and multi - agents realize coordination of multiple intersections to eliminate congestion . based on recursive modeling method and bayesian learning that enables an agent to select his rational action by examining with other agents by modeling their decision making in conjunction with dynamic belief update . based on this method , a simplified multi - agent traffic control system is established and the results demonstrate its effectiveness . it is very important for its
本文中提出一种城市交通智能控制系统，针对城市交通网络中相邻交叉口的交通流可能相互冲突，即局部交通流的优化可能引起其他区域交通状况的恶化的问题，采用多智能体协调控制方法来协调相邻交叉口处的控制信号消除网络中的交通拥塞.提出以一个智能体的方式实现一个信号灯交叉口控制，对多个信号灯交叉口形成的交通网络采用多智能体协调控制的方式实现网络流量优化来消除拥塞.文中提出由递归建模和改进的贝叶斯学习相结合的多智能体系统来使智能体可以确定其他智能体的准确模型并实时更新信息，并基于上述方法在简单的交通网络模型上建立了多智能体交通控制系统，仿真结果表明了方法的有效性，对实现智能交通系统有重要意义 |
| 10. | Elaborate process descriptions of evaluating offers , belief revision and proposing counteroffers are presented , in particular , we analyze the use of bayesian learning and reinforcement learning in negotiation process , restructuring the traditional q - learning into a dynamic q - leaming algorithm by introducing current beliefs and recency exploration bonus
在该谈判模型的基础上引入学习机制，并分别对评估提议、更新信念、生成提议等谈判过具有学习机制的电子商务自动谈判研究摘要程作了详细阐述，重点分析了贝叶斯学习和强化学习技术在自动谈判中的应用。 |
