Impact of feature scaling on machine learning models for the diagnosis of diabetes
Due to its high prevalence and incidence, diabetes is considered significant public health.
Since diabetes has no known cure, early diagnosis plays a vital role in effectively managing …
Since diabetes has no known cure, early diagnosis plays a vital role in effectively managing …
Tuning OER electrocatalysts toward LOM pathway through the lens of multi-descriptor feature selection by artificial intelligence-based approach
From the thermodynamic and kinetic viewpoints, the oxygen evolution reaction (OER) is
central to the production of hydrogen through electrocatalytic water splitting process. As a …
central to the production of hydrogen through electrocatalytic water splitting process. As a …
Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection
Predictions of Earth skin temperature (EST) can provide essential information for diverse
engineering applications such as energy harvesting and agriculture activities. Several …
engineering applications such as energy harvesting and agriculture activities. Several …
A novel hybrid optimization approach for fault detection in photovoltaic arrays and inverters using AI and statistical learning techniques: a focus on sustainable …
Fault detection in PV arrays and inverters is critical for ensuring maximum efficiency and
performance. Artificial intelligence (AI) learning can be used to quickly identify issues …
performance. Artificial intelligence (AI) learning can be used to quickly identify issues …
An overview of streamflow prediction using random forest algorithm
Since the first application of Artificial Intelligence in the field of hydrology, there has been a
great deal of interest in exploring aspects of future enhancements to hydrology. This is …
great deal of interest in exploring aspects of future enhancements to hydrology. This is …
Qualitative prediction of Thymoquinone in the high‐performance liquid chromatography optimization method development using artificial intelligence models coupled …
In this study, three various artificial intelligence‐based models were employed including two
non‐linear namely; Hammerstein–Wiener, the neuro‐fuzzy model, and a trivial linear multi …
non‐linear namely; Hammerstein–Wiener, the neuro‐fuzzy model, and a trivial linear multi …
Insight into soft chemometric computational learning for modelling oily-wastewater separation efficiency and permeate flux of polypyrrole-decorated ceramic-polymeric …
Reliable modeling of oily wastewater emphasizes the paramount importance of sustainable
and health-conscious wastewater management practices, which directly aligns with the …
and health-conscious wastewater management practices, which directly aligns with the …
Performance of hybrid neuro-fuzzy model for solar radiation simulation at Abuja, Nigeria: a correlation based input selection technique
OE Omeje, HS Maccido… - Knowledge …, 2021 - … journals.publicknowledgeproject.org
Abstract Solar Radiation (Rs) simulations for specific locations are critical for guiding
decisions about the design and operation of solar energy conversion devices. The …
decisions about the design and operation of solar energy conversion devices. The …
Evaluation of the thyroid cancer treatment techniques with fuzzy VIKOR
Thyroid cancer is the most common endocrine malignancy associated with follicular or non-
follicular thyroid cells. While ionizing radiation is a significant risk factor for thyroid cancer …
follicular thyroid cells. While ionizing radiation is a significant risk factor for thyroid cancer …
Deep learning and tree-based models for earth skin temperature forecasting in Malaysian environments
Abstract Predicting the Earth Skin Temperature (TS) using artificial intelligence (AI) has the
potential to offer valuable insights into environmental changes and their impacts. TS has …
potential to offer valuable insights into environmental changes and their impacts. TS has …