With the development of new energy power systems, estimation parameters photovoltaic (PV) models has become increasingly important. Weather changes are random; therefore, in PV output periodic and nonlinear. Traditional prediction methods based on linearity, relying only a time series is not feasible. Consequently, metaheuristic algorithms have received considerable attention to extract solar c...

In order to make a robot track desired trajectory with high precision and steady gait, novel intelligent controller was designed based on new mechanical structure optimized foot trajectory. Kinematics models in terms of the D-H method were established analyze relationship between angle driving joint position. Inspired by dog’s diagonal trot flat terrain, planning swing support phases without im...

NMT (Neural Machine Translation) is an innovative approach in the field of machine translation, contrast to SMT (statistical translation) and Rule-based techniques which has resulted annotable improvements. This because able overcome many shortcomings that are inherent traditional approaches. The Development grown tremendously recent years but performance remain under optimal when applied low r...

A deregulated electricity market provides open access to all players. In an open-access power market, the system operator is responsible for ensuring that contracted dispatched. However, if this results in line flows exceed their acceptable range, then it could threaten system’s security. Therefore, checks congestion as flow exceeds its limit. For management, applies different curtailment strat...

In recent years, optimization techniques have been developed to improve accuracy and reduce execution time. The moth flame technique (MFO) adapts behavior. This design is based on the moth's transverse orientation. Over long distances, they maintain a fixed angle with respect moon at night. They spiral around lights, however. Moths are trapped in deadly as light approaches; eventually, all conv...

Abstract Technical analysis indicators are popular tools in financial markets. These help investors to identify buy and sell signals with relatively large errors. The main goal of this study is develop new practical methods fake obtained from technical the precious metals market. In paper, we analyze these different ways based on recorded for 10 months. novelty research propose hybrid neural ne...

An enhanced version of the moth flame optimization algorithm is proposed in this paper for rapid and precise parameter extraction solar cells. The OBLVMFO algorithm’s novelty lies primarily improved search strategies, where two modifications are to maintain a proper balance between exploration exploitation. Firstly, an opposition-based learning mechanism employed initialize population purpose e...

Due to the unexpected breakdowns that can happen in various components of a production system, failure reach targets and interruptions process are not surprising. Since this issue remains for manufactured products, halting results loss profitability or demand. In study, address number challenges associated with management crucial spare parts inventory, mathematical model is suggested determinat...

In the online social networks, blogs, microblogs, bookmarking services and sharing sites, various web forum pages; of knowledge, opinions, ideas, etc. are spreading very quickly. This situation brings dangerous problems in networks. One these is hate speech detection (HSD) problem which covering issues such as insults, swearing, humiliation, discrimination, exclusion, detest, abhor, blast, damn...

The impact effect is a crucial issue in civil engineering and has received considerable attention for decades. For the first time, this study develops hybrid machine learning models that integrate novel Extreme Gradient Boosting (XGB) model with Particle Swam Optimization (PSO), Grey Wolf Optimizer (GWO), Moth Flame (MFO), Jaya (JA), Multi-Verse (MVO) algorithms predicting permanent transverse ...