Artificial intelligence education (AIEd) is defined in the field of education as the utilization of artificial intelligence. There are currently many AIEd-driven applications in schools and universities. This paper applies an artificial intelligence module combined with the knowledge recommendation to the system and develops an online English teaching system in comparison with the common teaching auxiliary system. The method of English teaching is useful in investigating the potential internal connections between evaluation outcomes and various factors. This article develops deep learning-assisted online intelligent English teaching system that utilizes to create a modern tool platform to help students improve their English language teaching efficiency in line with their mastery of knowledge and personality. The decision tree algorithm and neural networks have been used and to generate an English teaching assessment implementation model based on decision tree technologies. It provides valuable data from extensive information, summarizes rules and data, and helps teachers to improve their education and the English scores of students. This system reflects the thinking of the artificial intelligence expert system. Test application demonstrates that the system can help students improve their learning efficiency and will make learning content more relevant. Besides, the system How to cite this article: Sun Z, Anbarasan M, Praveen Kumar D. Design of online intelligent English teaching platform based on artificial intelligence techniques.

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Mobile ad-hoc network (MANET) is a gathering of portable nodes that works without foundation or central administration. Because of the accessibility of little and cheap remote conveying nodes, MANETs can be utilized as a part of different applications, for example, front line correspondence and debacle alleviation applications. Energy consumption is an important issues in MANET because the mobile nodes are battery powered, hence diminishing system lifetime as batteries get depleted rapidly as nodes move and change their positions quickly crosswise over MANET. We propose an energy efficient channel aware routing algorithm for mobile ad-hoc networks, called energy efficient channel aware ad-hoc on-demand multipath distance vector routing (EECA-AOMDV). EECA-AOMDV addresses three vital prerequisites of mobile ad-hoc networks: energy effectiveness, unwavering quality and dragging out system lifetime. The proposed energy efficient channel mindful AOMDV (EECA-AOMDV) utilizes the channel normal nonfading span and nodal residual energy as directing metric to choose the stable route for way revelation. The key thought of the convention is to discover average channel nonfading duration and maximum nodal residual energy as routing metrics of each course during the time spent choosing way and sort the multi course by slipping channel nonfading duration and nodal leftover energy. KEYWORDS Adhoc On Demand Multipath Distance Vector Protocol (AOMDV), Adhoc On Demand Distance Vector Protocol (AODV), channel aware routing, energy efficient, Mobile Adhoc Network (MANET), multipath routing, nodal residual energy INTRODUCTIONMultihop remote systems, likewise called portable specially appointed systems (MANET), 1 are self -sorting out, self-arranging and quickly deployable remote systems. MANETs are made out of portable nodes which are allowed to move arbitrarily with the ability of changing its connects to different nodes every now and again. These systems don't require any current foundation or focal organization. Along these lines the system topology may change quickly and be unpredictable. Customary methodologies for multi-bounce protocol in portable specially appointed systems embrace one single dynamic way amongst source and goal nodes of a correspondence stream, commonly settled by routing protocol. Routing protocols 2-9 for a MANET which can be classified into three groups namely reactive, proactive, and hybrid.In MANET protocol stack has compromises of four layers like physical layer performs bit by bit transmission of packets, Network layer is responsible for transmitting of packet by identifying route between source to destination, transport layer is plays connection oriented and connection less transmission and Application layer is acting application protocol packets transmission. The difference between the wireless and wired communication is on the changes in Network layer based on the routing strategy.The classification of MANET routing protocols are divided into three types.1. Reactive protocol established the route disc...

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Artificial intelligence can open modern opportunities and potentials for smart education. Smart learning purposes at providing holistic learning to learners utilizing modern technologies to fully prepare them for a fast-evolving world where adaptability is vital. With the advancement of technologies and within modern society, smart education will pose several challenges, like educational structures, pedagogical theory, educational ideology, technology leadership, and teachers’ learning leadership. Therefore, in this paper, an Intelligent Knowledge-based recommender system (IKRS) has been proposed using artificial intelligence for smart education. The recommendation is generated by the genetic algorithm and K-nearest neighbor algorithm (KNN) utilizing the optimized weight attributes vectors that signify the learner’s opinions. The experimental results show that the suggested IKRS model enhances student-teacher interaction, student involvement level, learning quality and predicts students’ learning style compared to other existing methods.