Titlebook: Soft Computing for Problem Solving 2019; Proceedings of SocPr Atulya K. Nagar,Kusum Deep,Kedar Nath Das Conference proceedings 2020 Springe

长矛

An Upgraded Differential Evolution via Memory-Based Mechanism for Economic Dispatch,(3, 6 and 15 unit) of economic dispatch (ED) problem. Experimental results prove that the proposed technique produces faster and more accurate solutions than traditional DE and PSO with the other state-of-the-art algorithms.

Formidable

Some Applications of Generalized Fuzzy ,-Closed Sets,interrelationships among these newly defined fuzzy sets with the existing ones. As an application, we introduce and study some new classes of spaces called fuzzy .-. spaces, fuzzy .-. space and fuzzy .-.-. space.

他去就结束

Paradox

AMPLE

Performance Analysis of Whale Optimization Algorithm Based on Strategy Parameter,ped heuristic algorithm which has strategy parameter . that decreases linearly from 2 to 0 as iteration increases. In this paper, two algorithms, modified whale optimization algorithm-1 (MWOA-1) and modified whale optimization algorithm-2 (MWOA-2), have been proposed based on the variation of the st

变化

占卜者

,Comparison of PSO and Sequential Search Algorithms for Improvisation of Entropy-Based Ear Localizat is a challenging one. In this paper, the performance of ear localization using optimization techniques such as entropy-based particle swarm optimization (PSO) and sequential search algorithms such as sequential forward selection (SFS) and sequential backward selection (SBS) are evaluated on roughly

Accomplish

An Upgraded Differential Evolution via Memory-Based Mechanism for Economic Dispatch,emory concept of PSO, the proposed DE is termed as ‘memory-based DE’ where new mutation and crossover operators are introduced. This proposed technique is validated on three typical benchmark functions namely, Rosenbrock, Rastrigrin and Griewank, and then implemented on three different test systems

buoyant

bizarre

Multi-Headed Self-Attention-based Hierarchical Model for Extractive Summarization,ions from an RNN (GRU). The model is hierarchical and learns the sentence and document representations hierarchically. It achieves performance better or comparable to the earlier such models. The paper establishes the utility of multi-headed attention in refining the representations and capturing th