Control of Static and Dynamic Parameters by Fuzzy Controller to Optimize Friction Stir Spot Welding Strength

Coatings, Journal Year: 2022, Volume and Issue: 12(10), P. 1442 - 1442

Published: Sept. 30, 2022

Solid-state welding is a derivative of the friction stir spot (FSSW) technique, which has been developed as new method for joining aluminum alloys. FSSW variant linear intended to deal with lightweight alloy resistance (RSW) and riveting. Tensile strength refers material’s ability withstand excessive stress when being stretched or pulled before necking; it expressed in terms force per unit area. The tensile affected by dynamic static parameters. control parameters studied this paper optimize strength. A fuzzy logic system used process approach that can be field. obtained results prove an easy inexpensive technology prediction optimization FSSW. Furthermore, show efficacy adequacy proposed system.

Language: Английский

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Fertiliser cost prediction in European Union farms: Machine-learning approaches through artificial neural networks

Open Agriculture, Journal Year: 2023, Volume and Issue: 8(1)

Published: Jan. 1, 2023

Abstract Machine-learning methodologies are part of the artificial intelligence approaches with several applications in different fields science and dimensions human life. These techniques appear frameworks digital transition, where smart technologies bring relevant contributions, such as improving efficiency economic sectors. This is particularly important for sectors agriculture to deal challenges created context climate changes. On other hand, machine-learning not easy implement, considering complexity algorithms associated. Taking this into account, main objective research present a model predict fertiliser costs European Union (EU) farms through neural network analysis. assessment may provide information farmers policymakers current scenario concerns identify strategies mitigate environmental impacts, including those from agricultural sector respective use chemical resources. To achieve these objectives, statistical EU regions Farm Accountancy Data Network was considered period 2018–2020. The findings obtained show relative errors between 0.040 0.074 (showing good accuracy) importance total utilised area output costs.

Language: Английский

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Benthic Macroinvertebrate Communities as Indicator of the Water Quality of a Suburban Stream in the Littoral Region of Cameroon

Pollutants, Journal Year: 2024, Volume and Issue: 4(2), P. 251 - 262

Published: May 7, 2024

As bioindicators, benthic macroinvertebrates are often used to assess stream quality. Based on standard hydrobiological study techniques, the physicochemical and biological health status of Missolé was assessed. Waters were found be slightly acidic (pH: 6.23–6.26) well-oxygenated (O2: 69.80–76.80%), with low values temperature (T°: 23.60–24° C), turbidity (49.40–88.40 FTU) mineralized ions (NH4+: 0–1.19 mg/L; NO2-: 0–1.61 NO3-: 0.02–6.80 mg/L). Concerning aquatic invertebrate communities, a total 489 individuals, grouped in two classes, eight orders 35 families, all belonging phylum Arthropoda, collected identified. The class Insecta most diversified, seven 32 while that Crustacea had only one order three families. Overall, accounted for 52.35% abundance, Decapod 47.65%. predominant families Palaemonidae, Dytiscidae Atyidae. Shannon Weaver (H’) Piélou’s evenness (J) indices high at stations showed slight decrease from upstream downstream. In same vein, Hilsenhoff Biotic Index (HBI) classified water quality as medium. this suburban ecosystem offers moderately favorable living conditions biota.

Language: Английский

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Application of WASP model to assess the benefits of sewer construction on river water quality in Taoyuan City — a case study of the Dahan River, Nankan River, and Laojie River

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: July 19, 2024

In order to improve river water quality, the most effective approach is control pollution sources and reduce amount of discharged into rivers. This study utilizes Water Quality Analysis Simulation Program (WASP) model simulate quality Dahan River, Nankan Laojie River in Taoyuan City. After simulating short, medium, long-term effects sewer construction (i.e., household connection rates) on improvement, as well greenhouse gas emissions, analysis reveals several key findings. Under government improvement schemes aimed at increasing rates sanitary sewers, expected have continuous good quality; after 2032, due increases rates, index Dakuaixi Bridge monitoring station from severely-polluted moderately-polluted; ammonia nitrogen (NH₃-N) biochemical oxygen demand (BOD₅) projected decrease both Zhongzheng Xucuogang No. 1 stations. Furthermore, affects emissions. results indicate that increase, emissions along all three rivers will decrease, thereby reducing energy associated with wastewater treatment facilities benefitting efforts Taiwan geared toward achieving net zero

Language: Английский

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Predicting iron contents in the Tamra-Douahria mining site using a deep neural network approach

Journal of Taibah University for Science, Journal Year: 2024, Volume and Issue: 18(1)

Published: Dec. 4, 2024

The well-known Douahria-Tamra mining site is characterized by the presence of deposits with high variability in composition, colour, and structural-textural peculiarities, especially exploitable layers. Thus, understanding underlying reasons for this heterogeneity crucial to optimize extraction processes, ensuring consistent product quality, maximizing resource utilization. This was motivation beyond attempt allocated shed light on behaviour iron other related ores district. Iron content estimated from measured lead, zinc, manganese, silica arsenic using unsupervised machine learning tools (HCA PCA) deep neural network. For purpose, 357 iron-rich samples collected Tamra-Douahria sub-district were used train, test validate obtained models. Out 357, 285 data sets selected training algorithm while 72 points model testing validation. Input variables included lead (Pb), zinc (Zn), manganese (Mn), (As) (SiO2) contents, (Fe %) considered as output. Our results indicated a mean value (26.19%) perfectly predicted 26.09% DNN model. A cross-validation step necessary confirm robustness proposed models coefficient determination (R2). (R2 = 0.9978) Pearson correlation (0.999) low RMSE (0.975) which accurate predictions actual values. Therefore, robust predicting contents studied site.

Language: Английский

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