A Relevant Customer Identification Algorithm Based on the Internet Financial Platform

In order to improve the intelligent search capabilities of Internet financial customers, this paper proposes a search algorithm for Internet financial data. The proposed algorithm calculates the customers corresponding to the two selected financial platforms based on the candidate customer set selected from the seed dataset and combined with the restored social relationship. Moreover, it also calculates the similarity of each field between the pairs. Furthermore, this article proposes an entity customer classification model based on logistic regression. Through the SNC model, threshold propagation, and random propagation, the model is transformed into an algorithm that identifies the associated customers, eliminates redundant customers, and realizes associated user identification. Experimental results verify that pruning increases the accuracy of identifying related customers by 8.44%. The average sampling accuracy of the entire customer association model is 79%, the lowest accuracy is 40%, and the highest is 1. From the sampling results, the overall recognition effect of the model reaches the expected goal.

Study of Intelligent Search Engine of Energy Industry Based on BERT Semantic Model

Based on a variety of heterogeneous data of energy enterprises, this paper provides an intelligent search method based on the Bert preprocessing model. This paper provides a method of intention recognition based on the combination of template matching and text classification, which involves machine learning, deep learning and other fields of artificial intelligence. First, the preprocessing model Bert is used to rewrite the natural language into a vector based on syntax. Then, the information extraction technology is used to extract the structured and machine understandable information from the problem to provide parameters for intention processing. The intention recognition technology used in this paper first uses template matching method, and then uses text classification method. Finally, the effects of various methods are compared through experimental examples.

Towards Personalized Medication

The paper describes some aspects of precision medicine and shows the importance of pharmacokinetics and pharmacodynamics for the therapeutic drug monitoring and model-informed precision dosing. A key element in the design of the pharmacokinetics and pharmacodynamics (PKPD) models is relevant literature search that represents an essential step in the procurement and validation of a new drug. Available search engine resources do not offer specific functionalities that are required for efficient and relevant search in reliable literature sources. We present a prototype of such an intelligent search engine and show its results on real project data.

Intelligent search for accurate solutions to the planning open-pit mining

A method of intelligent search for accurate solutions to the planning of open-pit mining has been developed. The method is implemented within the framework of the Constraint Programming Paradigm that allows us to process heterogeneous qualitative and quantitative constraints (in particular, economic, technological, etc.) simultaneously, as well as to maintain the model of subject domain being developed which is open to adding new constraints or deleting existing constraints. Various constraints can be added to the model, including those for which it is difficult to find a suitable analytical expression. In contrast to existing methods of local search the proposed method systematically explores the search space. The method allows us to find a global optimum in large dimensional spaces that describe practically significant problems arising in production. Currently, to solve this problem, the methods of integer linear programming are widely used. But its fundamental disadvantage is the need to represent all the constraints in the form of linear equalities and inequalities. However, in practice, some combinatorial optimization problems cannot be linearized and solved using traditional methods of mathematical programming. The developed method is illustrated by the example of a three-dimensional problem of finding the position of an intermediate pit wall by the processing periods taking into account the specified performance for mineral and overburden rocks and the objective profit function taking into account discounting. The types of constraints necessary for modeling the problem under consideration are identified. The possibility of applying the existing inference procedures on constraints is considered for these types. The method proposed makes it possible to obtain accurate solutions due to the intellectualization of the solution process by using highly efficient algorithms of reducing the search space for each type of constraints and specialized heuristics for pruning unpromising alternatives in the search tree.

Intelligent Search of Values for a Controller Using the Artificial Bee Colony Algorithm to Control the Velocity of Displacement of a Robot

The optimization is essential in the engineering area and, in conjunction with use of meta-heuristics, has had a great impact in recent years; this is because of its great precision in search of optimal parameters for the solution of problems. In this work, the use of the Artificial Bee Colony Algorithm (ABC) is presented to optimize the values for the variables of a proportional integral controller (PI) to observe the behavior of the controller with the optimized Ti and Kp values. It is proposed using a robot built using the MINDSTORMS version EV3 kit. The objective of this work is to demonstrate the improvement and efficiency of the controllers in conjunction with optimization meta-heuristics. In the results section, we observe that the results improve considerably compared to traditional methods. In this work, the main contribution is the implementation of an optimization algorithm (ABC) applied to a controller (PI), and the results are tested to control the movement of a robot. There are many papers where the kit is used in various domains such as education as well as research for science and technology tasks and some real-world problems by engineering scholars, showing the acceptable result.

Decentralized Intelligent Search of Tourist Routes Based on Check-In Data

The location social network generates a large amount of data; these dada reflect the user's preferences and the popularity of the route, and a new model is provided for travel route search. Based on this demand, a problem of local distributed travel route search is proposed for group users. In this problem, the personal preferences of group users are combined, and an access route is found with partial POI (point of interest) and the largest group profit. The check-in data are used to generate a POI transfer relationship diagram based on the user's transfer between POIs, and route search is performed on the relationship diagram. In order to improve the search efficiency, a two-layer transfer relationship diagram is designed according to the popularity and transfer relationship of POI, the POI is generalized, and a hierarchical query is realized. A branch and bound search strategy optimization algorithm is designed, and the control relationship between nodes is used for pruning; the search efficiency of the algorithm is further improved.

Applied Research of Knowledge in the Field of Artificial Intelligence in the Intelligent Retrieval of Teaching Resources

In the development process of education informatization, digital teaching resources continue to grow, and how to manage and organize massive teaching resources has become a key issue for teaching staff. An efficient and accurate search system is an important part of the teaching resource service system. The use of intelligent search engines can search teaching resources comprehensively and efficiently, and the artificial intelligence search engine provides a reliable and convenient solution for the design and development of intelligent search systems. The article analyzes the design principles and technical standards of the intelligent search system, expounds the system’s functional architecture and database design, and introduces the realization process and principles of the search system. By analyzing the characteristics of basic education resources and existing automatic abstracting methods, this paper proposes to integrate the calculated feature word weights in the field of basic education into the algorithm for calculating the weights of abstract sentences and simultaneously examine the sentence position, sentence length, and other texts. There is an automatic summarization algorithm for surface statistics. This article also introduces the search design ideas and implementation steps based on artificial intelligence, makes a scientific evaluation and summary of the actual situation of the automatic abstract system running in the basic education resource search engine, and looks forward to the next improvement work.