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Intelligent collision warning system based on fuzzy logic and neural network technologies.

机译：基于模糊逻辑和神经网络技术的智能碰撞预警系统。

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The recent technological changes in computer and industrial control systems have been steadily extending the capabilities to handle a broad range of complex systems. The emergence and development of computer technology and intelligent systems during the past few decades have created a highly promising direction in the field of artificial intelligence. It is increasingly difficult to describe any real system as the level of complexity continues to increase. A combination of systems and techniques are necessary to solve many complex problems. This new direction involves the use of fuzzy logic and artificial neural network theory to enhance the ability of intelligent systems that can learn from experience and to adapt to changes in an environment of uncertainty and imprecision.; The Intelligent Automotive Collision Warning System was developed as a rule-based system by integrating a fuzzy logic controller with artificial neural network software. The Intelligent Automotive Collision Warning system constantly monitors the speed of the vehicle and the distance of any object in front of the vehicle using an ultrasonic ranging module to warn the operator to maintain a safe operating distance by using fuzzy logic theory and artificial neural network software.; Descriptive statistics was used for collecting and organizing the data. Inferential statistics was used to prove the hypotheses based on the results of the collected data. NeuFuz4 software was used to train the neural network and to optimize the fuzzy rule-base.; The fuzzy logic technology provided a means of converting a linguistic control strategy to operate the warning system. The input/output relationship was defined by fuzzy membership functions which enabled the numerical inputs to be expressed as fuzzy variables using linguistic terms. A new fuzzy logic operator was also developed to optimize the fuzzy input/output relationship.
机译：计算机和工业控制系统中的最新技术变化已经稳定地扩展了处理各种复杂系统的能力。在过去的几十年中，计算机技术和智能系统的出现和发展为人工智能领域创造了非常有前途的方向。随着复杂程度的不断提高，描述任何实际系统变得越来越困难。系统和技术的结合对于解决许多复杂的问题是必要的。这个新方向涉及使用模糊逻辑和人工神经网络理论来增强可以从经验中学习并适应不确定性和不精确性环境变化的智能系统的能力。通过将模糊逻辑控制器与人工神经网络软件集成在一起，将智能汽车碰撞预警系统开发为基于规则的系统。智能汽车碰撞预警系统使用超声波测距模块不断监控车辆的速度和任何物体在车辆前方的距离，以通过使用模糊逻辑理论和人工神经网络软件来警告驾驶员保持安全的行驶距离。 ;描述性统计用于收集和组织数据。推论统计用于基于收集的数据的结果证明假设。 NeuFuz4软件用于训练神经网络并优化模糊规则库。模糊逻辑技术提供了一种转换语言控制策略以操作警告系统的方法。输入/输出关系由模糊隶属度函数定义，该函数使数值输入可以使用语言术语表示为模糊变量。还开发了一种新的模糊逻辑算子来优化模糊输入/输出关系。

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