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Amidst impending climate change and enhanced pollution levels around the globe, the need of the hour is to develop bio-based materials that are sustainable and possess comparable performance properties to their synthetic counterparts. In light of the aforementioned, numerous investigations are being conducted to identify, process, and create materials that are concurrently innocuous towards the environment and have superior properties. This book is a collection of such scientific articles that propagate novel ideas for the development of polymeric composite materials, which have application potential in numerous fields such as medicine, automobile, aviation, construction, etc. It also contains a pedagogical article that proposes some strategies to continue experimental research during pandemics. This book will provide readers a quick glance into recent developments regarding polymeric materials and will encourage them to propagate these research ideas further.

History of engineering & technology --- solid urban waste --- formaldehyde --- durability --- electrical properties --- mechanical properties --- recycling --- epoxy resin --- flammability --- heat release rate --- microscale combustion calorimetry --- multiple linear regression --- adaptive neuro-fuzzy inference system --- polyvinyl alcohol (PVA) --- bionanocomposites --- nanomechanical behaviour --- thin films --- particle size --- model free --- model fitting --- avrami-eroféev --- DAEM --- superhydrophobic surfaces --- self-healing --- natural hierarchical microstructures --- wood --- bio-composite --- linear low density polyethylene --- performance --- straws --- biocomposites --- nanofibers --- electrospinning --- cell culture --- graphene oxide --- barrier properties --- poly(lactic acid) --- clay --- nanocomposite --- permeability --- bacterial cellulose --- metal organic framework --- adsorption --- chitosan --- composite nanofibers --- silk fibroin --- polycaprolactone --- Taguchi --- rheological properties --- DMA --- injection molding --- thermal properties --- natural fibers --- biochar --- carbon fillers --- nanocomposites --- flame retardants --- fire --- PHB --- natural fiber --- compatibilizer --- cellulose --- biocomposite --- solid urban waste --- formaldehyde --- durability --- electrical properties --- mechanical properties --- recycling --- epoxy resin --- flammability --- heat release rate --- microscale combustion calorimetry --- multiple linear regression --- adaptive neuro-fuzzy inference system --- polyvinyl alcohol (PVA) --- bionanocomposites --- nanomechanical behaviour --- thin films --- particle size --- model free --- model fitting --- avrami-eroféev --- DAEM --- superhydrophobic surfaces --- self-healing --- natural hierarchical microstructures --- wood --- bio-composite --- linear low density polyethylene --- performance --- straws --- biocomposites --- nanofibers --- electrospinning --- cell culture --- graphene oxide --- barrier properties --- poly(lactic acid) --- clay --- nanocomposite --- permeability --- bacterial cellulose --- metal organic framework --- adsorption --- chitosan --- composite nanofibers --- silk fibroin --- polycaprolactone --- Taguchi --- rheological properties --- DMA --- injection molding --- thermal properties --- natural fibers --- biochar --- carbon fillers --- nanocomposites --- flame retardants --- fire --- PHB --- natural fiber --- compatibilizer --- cellulose --- biocomposite

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• Reference Manager
• EndNote
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Amidst impending climate change and enhanced pollution levels around the globe, the need of the hour is to develop bio-based materials that are sustainable and possess comparable performance properties to their synthetic counterparts. In light of the aforementioned, numerous investigations are being conducted to identify, process, and create materials that are concurrently innocuous towards the environment and have superior properties. This book is a collection of such scientific articles that propagate novel ideas for the development of polymeric composite materials, which have application potential in numerous fields such as medicine, automobile, aviation, construction, etc. It also contains a pedagogical article that proposes some strategies to continue experimental research during pandemics. This book will provide readers a quick glance into recent developments regarding polymeric materials and will encourage them to propagate these research ideas further.

solid urban waste --- formaldehyde --- durability --- electrical properties --- mechanical properties --- recycling --- epoxy resin --- flammability --- heat release rate --- microscale combustion calorimetry --- multiple linear regression --- adaptive neuro-fuzzy inference system --- polyvinyl alcohol (PVA) --- bionanocomposites --- nanomechanical behaviour --- thin films --- particle size --- model free --- model fitting --- avrami–eroféev --- DAEM --- superhydrophobic surfaces --- self-healing --- natural hierarchical microstructures --- wood --- bio-composite --- linear low density polyethylene --- performance --- straws --- biocomposites --- nanofibers --- electrospinning --- cell culture --- graphene oxide --- barrier properties --- poly(lactic acid) --- clay --- nanocomposite --- permeability --- bacterial cellulose --- metal organic framework --- adsorption --- chitosan --- composite nanofibers --- silk fibroin --- polycaprolactone --- Taguchi --- rheological properties --- DMA --- injection molding --- thermal properties --- natural fibers --- biochar --- carbon fillers --- nanocomposites --- flame retardants --- fire --- n/a --- PHB --- natural fiber --- compatibilizer --- cellulose --- biocomposite --- avrami-eroféev

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Artificial intelligence techniques, such as expert systems, fuzzy logic, and artificial neural network techniques have become efficient tools in modeling and control applications. For example, there are several benefits in optimizing cost-effectiveness, because fuzzy logic is a methodology for the handling of inexact, imprecise, qualitative, fuzzy, and verbal information systematically and rigorously. A neuro-fuzzy controller generates or tunes the rules or membership functions of a fuzzy controller with an artificial neural network approach. There are new instantaneous power theories that may address several challenges in power quality. So, this book presents different applications of artificial intelligence techniques in advanced high-tech electronics, such as applications in power electronics, motor drives, renewable energy systems and smart grids.

History of engineering & technology --- droop curve --- frequency regulation --- fuzzy logic --- the rate of change of frequency --- reserve power --- smart grid --- energy Internet --- convolutional neural network --- decision optimization --- deep reinforcement learning --- electric load forecasting --- non-dominated sorting genetic algorithm II --- multi-layer perceptron --- adaptive neuro-fuzzy inference system --- meta-heuristic algorithms --- automatic generation control --- fuzzy neural network control --- thermostatically controlled loads --- back propagation algorithm --- particle swarm optimization --- load disaggregation --- artificial intelligence --- cognitive meters --- machine learning --- state machine --- NILM --- non-technical losses --- semi-supervised learning --- knowledge embed --- deep learning --- distribution network equipment --- condition assessment --- multi information source --- fuzzy iteration --- current balancing algorithm --- level-shifted SPWM --- medium-voltage applications --- multilevel current source inverter --- motor drives --- phase-shifted carrier SPWM --- STATCOM --- electricity forecasting --- CNN–LSTM --- very short-term forecasting (VSTF) --- short-term forecasting (STF) --- medium-term forecasting (MTF) --- long-term forecasting (LTF) --- asynchronous motor --- linear active disturbance rejection control --- error differentiation --- vector control --- renewable energy --- solar power plant --- Data Envelopment Analysis (DEA) --- Fuzzy Analytical Network Process (FANP) --- Fuzzy Theory --- droop curve --- frequency regulation --- fuzzy logic --- the rate of change of frequency --- reserve power --- smart grid --- energy Internet --- convolutional neural network --- decision optimization --- deep reinforcement learning --- electric load forecasting --- non-dominated sorting genetic algorithm II --- multi-layer perceptron --- adaptive neuro-fuzzy inference system --- meta-heuristic algorithms --- automatic generation control --- fuzzy neural network control --- thermostatically controlled loads --- back propagation algorithm --- particle swarm optimization --- load disaggregation --- artificial intelligence --- cognitive meters --- machine learning --- state machine --- NILM --- non-technical losses --- semi-supervised learning --- knowledge embed --- deep learning --- distribution network equipment --- condition assessment --- multi information source --- fuzzy iteration --- current balancing algorithm --- level-shifted SPWM --- medium-voltage applications --- multilevel current source inverter --- motor drives --- phase-shifted carrier SPWM --- STATCOM --- electricity forecasting --- CNN–LSTM --- very short-term forecasting (VSTF) --- short-term forecasting (STF) --- medium-term forecasting (MTF) --- long-term forecasting (LTF) --- asynchronous motor --- linear active disturbance rejection control --- error differentiation --- vector control --- renewable energy --- solar power plant --- Data Envelopment Analysis (DEA) --- Fuzzy Analytical Network Process (FANP) --- Fuzzy Theory

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Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business and engineering processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to business information management in various current real-world problems by proposing crisp or uncertain multiple-criteria decision-making (MCDM) models and techniques, mostly including multi-attribute decision-making (MADM) approaches, in addition to a single paper proposing an interactive multi-objective decision-making (MODM) approach. Particular attention is devoted to information aggregation operators; 65% of papers dealt with this item. The topics of this Special Issue gained attention in Europe and Asia. A total of 48 authors from seven countries contributed to this Issue. The papers are mainly concentrated in three application areas: supplier selection and rational order allocation, the evaluation and selection of goods or facilities, and personnel selection/partner selection. A number of new approaches are proposed that are expected to attract great interest from the research community.

multiple attribute decision making --- maximizing deviation model --- interval multiplicative preference relations --- rough sets --- queuing systems --- fuzzy EDAS --- nonnegative normal neutrosophic number --- single-valued linguistic neutrosophic interval linguistic number --- order allocation --- multi-attribute decision-making (MADM) --- multi-criteria decision-making --- Pythagorean uncertain linguistic variable --- neutrosophic sets --- supplier --- green supplier --- trust interval --- ANFIS --- reliable group decision-making --- multiple criteria decision-making --- adaptive neuro-fuzzy inference system (ANFIS) --- multi-attribute group decision-making --- Pythagorean fuzzy set --- Muirhead mean --- subcontractor evaluation --- fuzzy sets --- group decision-making --- score function --- supplier selection --- unbalanced linguistic set --- projection model --- multiple criteria group decision-making --- warehouse --- multi-hesitant fuzzy sets --- Dombi operations --- interaction operational laws --- decision making --- MCDM --- multiple criteria decision making (MCDM) --- rough ANP --- MADM --- multiple attributes decision-making --- interactive approach --- weighted aggregation operator --- logistics --- rough analytical hierarchical process (AHP) --- linguistic cubic variable --- multiobjective optimization --- aggregation operators --- bi-directional projection model --- rough boundary interval --- prioritized average operator --- binary discernibility matrices --- Einstein operations --- hesitant probabilistic fuzzy Einstein aggregation operators --- multiple-criteria decision-making (MCDM) --- aggregation operator --- linguistic cubic variable Dombi weighted arithmetic average (LCVDWAA) operator --- linguistic cubic variable Dombi weighted geometric average (LCVDWGA) operator --- multi-attribute decision making --- trapezoidal fuzzy number --- rough number --- evidence theory --- uncertain group decision-making support systems --- desirability function --- deterministic finite automata --- rough weighted aggregated sum product assessment (WASPAS) --- hesitant probabilistic fuzzy element (HPFE) --- multiple attribute decision making (MADM). --- multiple attribute decision making --- maximizing deviation model --- interval multiplicative preference relations --- rough sets --- queuing systems --- fuzzy EDAS --- nonnegative normal neutrosophic number --- single-valued linguistic neutrosophic interval linguistic number --- order allocation --- multi-attribute decision-making (MADM) --- multi-criteria decision-making --- Pythagorean uncertain linguistic variable --- neutrosophic sets --- supplier --- green supplier --- trust interval --- ANFIS --- reliable group decision-making --- multiple criteria decision-making --- adaptive neuro-fuzzy inference system (ANFIS) --- multi-attribute group decision-making --- Pythagorean fuzzy set --- Muirhead mean --- subcontractor evaluation --- fuzzy sets --- group decision-making --- score function --- supplier selection --- unbalanced linguistic set --- projection model --- multiple criteria group decision-making --- warehouse --- multi-hesitant fuzzy sets --- Dombi operations --- interaction operational laws --- decision making --- MCDM --- multiple criteria decision making (MCDM) --- rough ANP --- MADM --- multiple attributes decision-making --- interactive approach --- weighted aggregation operator --- logistics --- rough analytical hierarchical process (AHP) --- linguistic cubic variable --- multiobjective optimization --- aggregation operators --- bi-directional projection model --- rough boundary interval --- prioritized average operator --- binary discernibility matrices --- Einstein operations --- hesitant probabilistic fuzzy Einstein aggregation operators --- multiple-criteria decision-making (MCDM) --- aggregation operator --- linguistic cubic variable Dombi weighted arithmetic average (LCVDWAA) operator --- linguistic cubic variable Dombi weighted geometric average (LCVDWGA) operator --- multi-attribute decision making --- trapezoidal fuzzy number --- rough number --- evidence theory --- uncertain group decision-making support systems --- desirability function --- deterministic finite automata --- rough weighted aggregated sum product assessment (WASPAS) --- hesitant probabilistic fuzzy element (HPFE) --- multiple attribute decision making (MADM).

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Artificial intelligence techniques, such as expert systems, fuzzy logic, and artificial neural network techniques have become efficient tools in modeling and control applications. For example, there are several benefits in optimizing cost-effectiveness, because fuzzy logic is a methodology for the handling of inexact, imprecise, qualitative, fuzzy, and verbal information systematically and rigorously. A neuro-fuzzy controller generates or tunes the rules or membership functions of a fuzzy controller with an artificial neural network approach. There are new instantaneous power theories that may address several challenges in power quality. So, this book presents different applications of artificial intelligence techniques in advanced high-tech electronics, such as applications in power electronics, motor drives, renewable energy systems and smart grids.

History of engineering & technology --- droop curve --- frequency regulation --- fuzzy logic --- the rate of change of frequency --- reserve power --- smart grid --- energy Internet --- convolutional neural network --- decision optimization --- deep reinforcement learning --- electric load forecasting --- non-dominated sorting genetic algorithm II --- multi-layer perceptron --- adaptive neuro-fuzzy inference system --- meta-heuristic algorithms --- automatic generation control --- fuzzy neural network control --- thermostatically controlled loads --- back propagation algorithm --- particle swarm optimization --- load disaggregation --- artificial intelligence --- cognitive meters --- machine learning --- state machine --- NILM --- non-technical losses --- semi-supervised learning --- knowledge embed --- deep learning --- distribution network equipment --- condition assessment --- multi information source --- fuzzy iteration --- current balancing algorithm --- level-shifted SPWM --- medium-voltage applications --- multilevel current source inverter --- motor drives --- phase-shifted carrier SPWM --- STATCOM --- electricity forecasting --- CNN–LSTM --- very short-term forecasting (VSTF) --- short-term forecasting (STF) --- medium-term forecasting (MTF) --- long-term forecasting (LTF) --- asynchronous motor --- linear active disturbance rejection control --- error differentiation --- vector control --- renewable energy --- solar power plant --- Data Envelopment Analysis (DEA) --- Fuzzy Analytical Network Process (FANP) --- Fuzzy Theory