Scaled conjugate gradient ANN for industrial sensors calibration

Othman, Karam M.Z.; Salih, Abdulkreem Mohammed

doi:10.11591/eei.v10i2.2738

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…Instead, it implements the trust region method. With this approach, the model's training cost is minimized and faster analyses can be done (Othman and Salih, 2021). In BR method, before the training, there is a pre-distribution of model parameters and this encodes the value of the parameter before seeing the data (Pillonetto et al, 2022).…”

Section: Prediction Of Cutting Forces In Cnc Slotmillingmentioning

confidence: 99%

Estimation of cutting forces in CNC slot-milling of low-cost clay reinforced syntactic metal foams by artificial neural network modeling

Bolat,

Özdoğan,

Çoban

et al. 2024

MMMS

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PurposeThis study aims to elucidate the machining properties of low-cost expanded clay-reinforced syntactic foams by using different neural network models for the first time in the literature. The main goal of this endeavor is to create a casting machining-neural network modeling flow-line for real-time foam manufacturing in the industry.Design/methodology/approachSamples were manufactured via an industry-based die-casting technology. For the slot milling tests performed with different cutting speeds, depth of cut and lubrication conditions, a 3-axis computer numerical control (CNC) machine was used and the force data were collected through a digital dynamometer. These signals were used as input parameters in neural network modelings.FindingsAmong the algorithms, the scaled-conjugated-gradient (SCG) methodology was the weakest average results, whereas the Levenberg–Marquard (LM) approach was highly successful in foreseeing the cutting forces. As for the input variables, an increase in the depth of cut entailed the cutting forces, and this circumstance was more obvious at the higher cutting speeds.Research limitations/implicationsThe effect of milling parameters on the cutting forces of low-cost clay-filled metallic syntactics was examined, and the correct detection of these impacts is considerably prominent in this paper. On the other side, tool life and wear analyses can be studied in future investigations.Practical implicationsIt was indicated that the milling forces of the clay-added AA7075 syntactic foams, depending on the cutting parameters, can be anticipated through artificial neural network modeling.Social implicationsIt is hoped that analyzing the influence of the cutting parameters using neural network models on the slot milling forces of metallic syntactic foams (MSFs) will be notably useful for research and development (R&D) researchers and design engineers.Originality/valueThis work is the first investigation that focuses on the estimation of slot milling forces of the expanded clay-added AA7075 syntactic foams by using different artificial neural network modeling approaches.

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Section: Prediction Of Cutting Forces In Cnc Slotmillingmentioning

confidence: 99%

Estimation of cutting forces in CNC slot-milling of low-cost clay reinforced syntactic metal foams by artificial neural network modeling

Bolat,

Özdoğan,

Çoban

et al. 2024

MMMS

View full text Add to dashboard Cite

show abstract

“…These topics covers the ways that human being recognizes, classifies, and takes decisions. Therefore, one can find applications in industry [1]- [3] information security [4], [5], and medical engineering [6]- [8]. The availability of several computer algorithms and systems based on artificial intelligent can be utilized to assist the medical decision process in order to ensure accuracy and precision [9]- [11].…”

Section: Introductionmentioning

confidence: 99%

“…on fibrat + statin) (1) 8) If (TG1 is good) and (TG2 is good) and (TG3 is good) then (decision is cont. on fibrat + statin) (1) 9) If (TG1 is bad) and (TG2 is bad) and (TG3 is bad) then (decision is add omega3 + statin + fibrate)(1)…”

mentioning

confidence: 99%

Therapeutic management of diseases based on fuzzy logic system- hypertriglyceridemia as a case study

Othman

Zeki²

2023

TELKOMNIKA

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The support systems for assisting clinical decision highly improve the quality and efficiency of the therapeutic and diagnostic treatment in medicine. The proper implementation of such systems can emulate the reasoning of health care professionals in such a way that suggest reasonable decisions on patient treatment. The fuzzy logic system can be considered as one of the efficient techniques for converting a complex decision tree that usually facing the physician into artificial intelligent procedure embedded in a computer program. So many properties in fuzzy logic system that can facilitate the process of medical diagnosis and therapeutic management. In this paper, a system for therapeutic management of hypertriglyceridemia was efficiently realized using a fuzzy logic technique. The obtained results had shown that the proposed fuzzy logic contributes a reliable managing procedure for assisting the physicians and pharmacist in treating the hypertriglyceridemia. Many different hypertriglyceridemia treatment cases showed a perfect matching decision between the standard guidelines and that given by the proposed system.

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Scaled conjugate gradient ANN for industrial sensors calibration

Cited by 2 publications

References 17 publications

Estimation of cutting forces in CNC slot-milling of low-cost clay reinforced syntactic metal foams by artificial neural network modeling

Estimation of cutting forces in CNC slot-milling of low-cost clay reinforced syntactic metal foams by artificial neural network modeling

Therapeutic management of diseases based on fuzzy logic system- hypertriglyceridemia as a case study

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