Computational Intelligence in Automotive Applications Episode 1 Part 2

Tham khảo tài liệu 'computational intelligence in automotive applications episode 1 part 2', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 4 Y. Zhang et al. pdf p d ptl hl Fig. 3. The probability distribution function of fixation duration under high and low workload Fixation duration the probability distribution function pdf of fixation duration under high workload p tfd hwi is multimodal as shown in Fig. 3. With collected ocular data one may estimate the conditional pdfs p tfd hwi and p tfd lwi and the prior probabilities for high and low workload P hwi and P lwi . With this knowledge standard Bayesian analysis will tell the probability of high workload given the fixation duration h _p fd lhwi p hwi __ p wl fd p tfdlhwl P hwl p tfdllwl P lwl 3 The Proposed Approach Learning-Based DWE We proposed a learning-based DWE design process a few years ago 17 18 . Under this framework instead of manually analyzing the significance of individual features or a small set of features the whole set of features are considered simultaneously. Machine-learning techniques are used to tune the DWE system and derive an optimized model to index workload. Machine learning is concerned with the design of algorithms that encode inductive mechanisms so that solutions to broad classes of problems may be derived from examples. It is essentially data-driven and is fundamentally different from traditional AI such as expert systems where rules are extracted mainly by human experts. Machine learning technology has been proved to be very effective in discovering the underlying structure of data and subsequently generate models that are not discovered from domain knowledge. For example in the automatic speech recognition ASR domain models and algorithms based on machine learning outperform all other approaches that have been attempted to date 19 . Machine learning has found increasing applicability in fields as varied as banking medicine marketing condition monitoring computer vision and robotics 20 . Machine learning technology has been implemented in the context of driver behavior modeling. Kraiss 21 showed .

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