The strength of college students' learning enthusiasm directly affects their effect. Studying and predicting has positive significance for improving students themselves education. Existing methods have not involved how to select extract features related enthusiasm, so it is difficult meet the needs prediction. Therefore, this article takes English as an example conduct a research on prediction ...

This study provides a teaching-learning-based optimization (TLBO) path planning method for an autonomous vehicle in cluttered environment, which takes into account smoothness and the possibility of collision with nearby obstacles. The problem is tackled as multiobjective order to plan efficient that allows travel autonomously crowded settings. TLBO algorithm is used find ideal path, goals fin...

The human has always been to find the best in all things. This Perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables and find the best acceptable answer Due to the limitations of the problem, So that the objective function is minimum or maximum. One of the ways inaccurate optimization is meta-heuristics so that Inspired by nature, ...

Assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. SSPCO optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. One of the things that smart algorithms are applied to solve is the problem ...

The article suggests an algorithm for regular classifier ensemble methodology. The proposed methodology is based on possibilistic aggregation to classify samples. The argued method optimizes an objective function that combines environment recognition, multi-criteria aggregation term and a learning term. The optimization aims at learning backgrounds as solid clusters in subspaces of the high...

Multi-objective optimization problems are currently gaining significant attentions from researchers because many real-world optimization problems consist of contradictory objectives. SPEA (Strength Pareto Evolutionary Algorithm) is one of the most successful multi-objective evolutionary algorithms for approximating the Pareto-optimal set for multiobjective optimization problems. In this paper, ...