Application of fuzzy inference techniques in the production of eco-friendly aminoplast based modified resins for plywood panel industries

Dey, Sanghamitra; Jana, Dipak Kumar; Khatua, Pijus Kanti; Mukherjee, Anupam

doi:10.1504/ijfcm.2019.100320

Cited by 4 publications

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“…In classical methods of optimization, it is difficult to solve the complex interactions between the variables and responses since it can handle the variation of only one parameter at a time, keeping other factors constant Dey et al 2019). Response surface methodology is one of the most user friendly, potable method to design experiments statistically.…”

Section: Introductionmentioning

confidence: 99%

Synthesis of potential bio-adsorbent from Indian Neem leaves (Azadirachta indica) and its optimization for malachite green dye removal from industrial wastes using response surface methodology: kinetics, isotherms and thermodynamic studies

et al. 2020

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The response surface methodology has been extended to study the adsorption of malachite green dye (MG) on Indian Neem leaf powder (NLP), Azadirachta indica. The study was experimented by varying the solution concentration from 10 to 100 mg/l. The removal percentage of MG was determined by spectrophotometer at wavelength of 618 nm. Design Expert 11.0 was used as a tool to study the optimal conditions of MG adsorption (applying 2-factorial interaction model of central composite design) and evaluation of interaction effects of different operating parameters including pH, time, solute concentration, temperature and adsorbent dosage. Numerical optimization helped to identify the optimal conditions for achieving the targeted dye removal of 95.493% when the pH, time, solute concentration, temperature and adsorbent amount were set at the range of 6.868, 36.4 min, 27.899 mg/l, 308.477 K, and 4.3475 g/l respectively. The experimental results indicate that the maximum adsorption capacity of NLP depends on various operating parameter like, pH, dye concentration, particle size of adsorbents and it's activation. It was noted that adsorption capacity of the NLP increases from 33.33 to 66.72 mg/g when it was activated with dilute HCl. The higher correlation coefficient value (R 2) of Langmuir isotherm 0.996 and lower p value (0.01203) indicate the fitness of the response surface 2FI model developed. Kinetic studies displayed the suitability of pseudo second order reaction for this adsorption process. The thermodynamic study show that the sorption process is exothermic and spontaneous in nature. It was observed that the adsorbent NLP in the form of fine powder are very effective for the removal of MG from its aqueous solution. The satisfactory values of regression coefficients at different temperature, and fittings of adsorption isotherms indicate that Indian NLP is a promising adsorbent for treatment of textile dyes.

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Section: Introductionmentioning

confidence: 99%

Synthesis of potential bio-adsorbent from Indian Neem leaves (Azadirachta indica) and its optimization for malachite green dye removal from industrial wastes using response surface methodology: kinetics, isotherms and thermodynamic studies

et al. 2020

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Optimization of Palm Oil Mill Effluent (POME) Solubilization Using Linguistic Fuzzy Logic and Machine Learning Techniques

Janková

Dostál

Jana

et al. 2023

Springer Proceedings in Mathematics &Amp; Statistics

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Ecological environment fuzzy networking system protection based on optical fiber intelligent network

Wang

2021

IFS

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The optical fiber network has the characteristics of providing users with wider bandwidth and supporting the changing needs of more users. At the same time, the optical fiber network can also reduce the network infrastructure investment. The traditional Ad Hoc On-demand Distance Vector (AODV) algorithm does not consider the impact of node movement on the network, and the link disconnection frequently occurs during the routing process. The ant colony algorithm based on swarm intelligence only considers the unique factor of pheromone concentration to find the optimal path through multiple iterations, which will increase the complexity of the algorithm and affect the route establishment delay. In response to the above problems, this paper proposes a routing algorithm based on fuzzy logic. The algorithm can comprehensively consider the three factors of node location, mobility and signal strength, and greatly reduces the complexity of the algorithm. This paper gives a detailed definition of profust reliability of the Ethernet Passive Optical Network (EPON) system for distribution network communication and obtains the profust reliability parameters based on Monte Carlo simulation. After that, the reliability of profust under different networking modes was simulated, and the influence of network scale, component failure rate, component repair time and other parameters on the reliability of EPON networking profust was analyzed. The fuzzy probist reliability analysis method uses analytical methods, which are commonly used to deal with end-to-end reliability analysis problems and has certain limitations. Profust reliability analysis treats the system as a whole, which is more suitable for the reliability of complex end-to-multi-end systems.

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Application of fuzzy inference techniques in the production of eco-friendly aminoplast based modified resins for plywood panel industries

Cited by 4 publications

References 0 publications

Synthesis of potential bio-adsorbent from Indian Neem leaves (Azadirachta indica) and its optimization for malachite green dye removal from industrial wastes using response surface methodology: kinetics, isotherms and thermodynamic studies

Synthesis of potential bio-adsorbent from Indian Neem leaves (Azadirachta indica) and its optimization for malachite green dye removal from industrial wastes using response surface methodology: kinetics, isotherms and thermodynamic studies

Optimization of Palm Oil Mill Effluent (POME) Solubilization Using Linguistic Fuzzy Logic and Machine Learning Techniques

Ecological environment fuzzy networking system protection based on optical fiber intelligent network

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