Academic literature on the topic 'Fashion trend forecasting'

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Journal articles on the topic "Fashion trend forecasting"

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Chiaroni, Keren Muriel. "Fashion and Design Trend-forecasting." International Journal of the Arts in Society: Annual Review 4, no. 4 (2009): 71–80. http://dx.doi.org/10.18848/1833-1866/cgp/v04i04/35670.

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Lopes, Maria Vieira. "The discourse of fashion change: Trend forecasting in the fashion industry." Fashion, Style & Popular Culture 6, no. 3 (October 1, 2019): 333–49. http://dx.doi.org/10.1386/fspc.6.3.333_1.

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Satrio, Akbar Adhi, Tri Hasdianto Hasdianto, and Amelinda Alysia A.V.K. "PERAN TRADISI DALAM TREND FORECASTING." Serat Rupa Journal of Design 4, no. 1 (January 16, 2020): 40–50. http://dx.doi.org/10.28932/srjd.v4i1.1959.

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This study is preliminary research of "The Trend Forecasting Translation Analysis in The Context of Craft". Trend Forecasting is a developed method that aims to predict future trends through research and analysis based on factual data of phenomena that occurs during certain time frames. The process includes analyzing various factors including technological development, lifestyle, also shifts of paradigm that form strategic decisions towards product design. However, the role of the trend forecast being applied to today’s craft designing process needs to be further reviewed. It is related to the fact where traditional elements are attached to all craft products, emphasized to be well-preserved in showing its characteristics of culture and tradition. This study seeks to map where the position of tradition takes place among the trend forecasting process through the analysis of a.) field studies in institutions and practitioners in the field of trend forecast; b.) comparative study of the position of tradition in the process of trend forecasting based on three kinds of literature namely ”The Trend Forecaster’s Handbook”, ”How to Research Trends”, and ”Fashion Forecasting”. In the scope of methods, the results of this study show that tradition stands as a significant data in the process of constructing a trend forecast. However, the perspective is not under the context of local culture but as the behavior of people.
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Chakraborty, Samit, S. M. Azizul Hoque, and S. M. Fijul Kabir. "Predicting fashion trend using runway images: application of logistic regression in trend forecasting." International Journal of Fashion Design, Technology and Education 13, no. 3 (September 1, 2020): 376–86. http://dx.doi.org/10.1080/17543266.2020.1829096.

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Ballmer, Amy, and Jennifer Tobias. "Trend forecasting: Collecting the history of the future." Art Libraries Journal 42, no. 1 (December 15, 2016): 19–25. http://dx.doi.org/10.1017/alj.2016.40.

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How do art and design libraries collect the history of the future? Trend forecasting literature presents exactly that challenge. These multifaceted print and digital publications, issued regularly and expensively by a handful of companies, are held by few libraries even as they influence everything from womenswear to computer games. We examine how libraries collect these materials and consider their role in the broader information landscape.First, we historically situate forecasting, looking to origins in colour charts, trade catalogues and international communications. Next, we look at the post-war institutionalization of trend forecasting, describing its role in the consolidation of a consumer-oriented supply chain.With the Fashion Institute of Technology as the case study, we then examine forecasting in context: how faculty incorporate it into pedagogy, how students engage with the materials and how librarians integrate critical thinking and information literacy into instruction. Practical matters such as cost, housing, long-term archiving and access are also addressed.We conclude with a forecast of forecasting, examining its move to digital formats and the challenge of meeting pedagogical needs that are at once rigorous (as accreditation demands) and creative (as schools promise), reflecting the mash-up wonder of today's fashion discourse.
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An, Hyosun, Sunghoon Kim, and Yerim Choi. "Sportive Fashion Trend Reports: A Hybrid Style Analysis Based on Deep Learning Techniques." Sustainability 13, no. 17 (August 24, 2021): 9530. http://dx.doi.org/10.3390/su13179530.

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This study aimed to use quantitative methods and deep learning techniques to report sportive fashion trends. We collected sportive fashion images from fashion collections of the past decades and utilized the multi-label graph convolutional network (ML-GCN) model to detect and explore hybrid styles. Based on the literature review, we proposed a theoretical framework to investigate sportive fashion trends. The ML-GCN was designed to classify five style categories, “street,” “retro,” “sexy,” “modern,” and “sporty,” and the predictive probabilities of the five styles of fashion images were extracted. We statistically validated the hybrid style results derived from the ML-GCN model and suggested an application method of deep learning-based trend reports in the fashion industry. This study reported sportive fashion by hybrid style dependency, forecasting, and brand clustering. We visualized the predicted probability for a hybrid style to a three-dimensional scale expected to help designers and researchers in the field of fashion to achieve digital design innovation cooperating with deep learning techniques.
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Kawinakrathiti, Komaek, Suphakant Phimoltares, and Patcha Utiswannakul. "Developing Forecasting Model in Thailand Fashion Market Based on Statistical Analysis and Content-Based Image Retrieval." International Journal of E-Entrepreneurship and Innovation 5, no. 1 (January 2015): 32–46. http://dx.doi.org/10.4018/ijeei.2015010103.

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Traditional trend forecasting process in Thailand fashion industry was challenged by a fast fashion. In this paper, the Content-Based Image Retrieval (CBIR) technique is utilized for retrieval of a fashion trendsetter in fast fashion influence. Firstly, six fashion theories were implemented as 12 variables affecting the trendsetter. Cluster analysis, and factor analysis approach were used to find out the source of a fashion trendsetter as well. Cluster analysis separated all samples into three groups with different fashion ways. Moreover, factor analysis technique grouped all variables into three important factors. From such techniques, Internet media clearly is the best source of a fashion trendsetter. In the authors' model, traditional forecasting sources were added up with a fast fashion influence from CBIR. Then, the CBIR was evaluated in terms of efficiency compared with a real fashion expert in the Thai fashion industry. From statistical test, spatial color distribution yields high efficiency in selecting similar fashion style as a fashion expert.
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DuBreuil, Mikayla, and Sheng Lu. "Traditional vs. big-data fashion trend forecasting: an examination using WGSN and EDITED." International Journal of Fashion Design, Technology and Education 13, no. 1 (January 2, 2020): 68–77. http://dx.doi.org/10.1080/17543266.2020.1732482.

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Yu, Yong, Chi-Leung Hui, and Tsan-Ming Choi. "An empirical study of intelligent expert systems on forecasting of fashion color trend." Expert Systems with Applications 39, no. 4 (March 2012): 4383–89. http://dx.doi.org/10.1016/j.eswa.2011.09.153.

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Bandlien, Charlotte Bik. "Post Luxury: Normcore as Node and Prism." APRIA Journal 1, no. 1 (February 1, 2020): 25–37. http://dx.doi.org/10.37198/apria.01.00.a5.

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'Normcore' was not only the most Googled fashion trend of 2014 but also the runner-up for neologism of the year by Oxford University Press. The phrase generated numerous headlines, such as "Normcore Is (or Is It?) a Fashion Trend (or Non-Trend or Anti-Trend)" in the Los Angeles Times in 2015 or "Everyone's Getting Normcore Wrong, Says Its Inventors" in Dazed in 2014, indicating a multi-faceted and intriguing phenomenon. This article employs the timing of post peak normcore to investigate a trend that surely entailed more than meets the eye. Described as "a unisex fashion trend characterized by unpretentious, normal-looking clothing" by Wikipedia, normcore was in fact not meant to be a trend at all, nor was it meant to be used to refer to a particular code of dress. Initially a spoof marketing term coined by the art collective/trend forecasting group K-Hole in 2013, normcore was originally a subversive concept, anticipating an alternative way forward, proposing anti-distinction as the radical new, analysed here as a mode beyond luxury—as 'post luxury'. Combining anthropology, consumption theory, and critical fashion theory with a practice-based insight informed by the author's background in trend analysis and brand planning as well as the art school context, this article attempts to frame and unpack normcore in order to speculate about the future of luxury.
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Dissertations / Theses on the topic "Fashion trend forecasting"

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Frohm, Pauline, and Kara Xenia Tucholke. "The trend forecasting paradox? : An exploratory study of the compatibility of trend forecasting and sustainability." Thesis, Högskolan i Borås, Akademin för textil, teknik och ekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-23475.

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Trend forecasting is perceived to be an essential service for fashion companies to use in order to stay competitive in the fast-paced fashion industry. Yet, in times of climate change, appointing new trends each season is a questioned practice. Since trend forecasting aligns with the inherent obsolescence of fashion’s constant change, forecasting seems to stand in paradox with the imperatives of sustainability. Thus, this thesis aims to explore the role of trend forecasting to understand its compatibility with environmental sustainability. The review of previous research depicts the evolution of the trend forecasting field and displays prominent literature within fashion and sustainability, which together displays an apparent research gap that this study aims to fill. The thesis follows an exploratory design pursuing a multiple case study strategy applied through eight semi-structured interviews with trend forecasters and a content analysis of WGSN online trend forecasts. Findings of this study validate the existence of a trend forecasting paradox while also demonstrating areas of compatibilities. Customized forecasting and long-term approaches were concluded as compatible practices and may be integrated into both long-term and seasonal forecasting. This study also recognizes a need to differ between forecasting sustainability and sustainable forecasting. This thesis is believed contribute to an under-researched area and aid the trend forecasting industry to realize its impact on sustainability, as well as suggesting approaches on how to further incorporate sustainable practices into their work.
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Steffie, Muvira Johanna. "Sustainability communication : Trend institutes’ influence on thedecision-making of a fashion designer." Thesis, Högskolan i Borås, Akademin för textil, teknik och ekonomi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-972.

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Purpose & research questions: The purpose of this paper is to investigate the roleand influence trend institutes have on the decision a designer makes in the designand development of a garment/product’s lifecycle. Theoretical approach: The theoretical framework is based on the theories ofsustainability and trends but also on previous studies and models concerning thefashion design process and the environmental aspects of a garment’s lifecycle. Research Approach: The research uses a qualitative method based on multiple casestudies as research design. Conclusion: This research reveals that trend institutes have little or no influence atall for small, independent and high-end fashion designers, especially in sustainablefashion design because trend institutes are not perceived as knowledgeable enough oradvocates, yet. However, it is important to bear in mind the need to maintain thepicture of the high-end fashion designer as the one and only fashion contributor.Furthermore, The research evidences that there is no such thing as sustainabilitycommunication at trend institutes.
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Sundqvist, Lovisa, and Annie Wrang. "Vikten att följa trender - en inköpares dilemma? : En tvärsnittsstudie om beslutsfattandet inom svenska modeföretags inköpsprocesser." Thesis, Högskolan i Borås, Akademin för textil, teknik och ekonomi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-173.

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Sedan millenniumskiftet förändrades modevärlden radikalt av fler säsonger, ökad mångfald av trender samtidigt som trendernas livslängds blev allt kortare. Hos inköparna på de stora klädbolagen ställs det idag ett allt större krav att veta vad som kommer att sälja i framtiden. Idag måste besluten tas snabbt så att kläderna hinner producera och levereras i tid innan modet hinner ändra sig. Som ett hjälpmedel för inköpare och designers om i vilken riktning modet kommer att gå finns trender som fungerar som ett avgränsat modeuttryck för att förmedla och tolka en viss stil och därmed ge en tydlig bild om vad som bör produceras och efterfrågas. Men eftersom internet har medfört en ökad acceleration av trender kan det upplevas svårt att veta vad som kommer sälja i framtiden och det är här ser vi trendbyråernas roll. Trendbyråer har en koordinerande roll på marknaden där de ger företag vägledning om förändringar i modet. Genom trendanalyser får företag en överblick hur riktningen i modet kommer att gå, förstå vilka globala influenser som påverkar modet och en reflektion kring hur allt återspeglas till modet. Vad gäller tidigare forskning av begreppen trender och trendbyråer vid beslutsfattande, har ingen omfattande undersökning tidigare gjorts vilket har medfört att vår uppsats känns värdefull för en mer förståelse kring ämnet. Avsikten med vår uppsats är att undersöka och analysera hur trender och trendanalyser har för betydelse vid beslutsfattande inom inköpsprocessens tidiga stadium hos svenska modeföretag. Studien har efter insamling av teori inom områdena beslut, trender och trendanalyser genomförts med en kvalitativ grund där insamling av det empiriska materialet har utgått från semistrukturerade intervjuer. Intervjuer har främst genomförts med respondenter som innehar en roll inom inköp på svenska modeföretag som ingår i beteckningen SME (Small medium Enterprises). Dessa företag är Ellos, Lindex, Gina Tricot och MQ. För att öka förståelsen kring trender och trendanalyser har intervjuer även genomförts med en trendanalytiker från Svenska Moderådet och en författare bakom boken Trendmakarna. Insamlad data har därefter analyserats och ställts mot teorier angående beslut, trender och trendanalyser i syfte att kunna uttala oss om hur inköpare ser på trender och trendbyråers betydelse vid beslutsfattande av inköp. De resultat som empirin bestått av ger indikationer på att trender har en betydande roll men att det både kan öka och minska på osäkerheter samt risker. Inköparna anser att det finns många risker med trendbaserade produkter men att trendanalyser vid beslutsfattande kan användas för att förstå riktningen modet går i för att därefter kunna anpassa inköpen genom volym, budget, material och leverantörer. Därmed kan de vara ett hjälpmedel för att minska på både ett besluts risk och osäkerhet, vilket bekräftar de teorier som tagits upp. Dock kan vi uttala oss om att beslutsfattande inom inköp inte bara baseras på trendanalyser utan andra faktorer och variabler spelar också in.
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Moschopoulos, Theodosios, and Sofia Dahlström. "Colour Forecasting and its managerial implications." Thesis, Högskolan i Borås, Institutionen Textilhögskolan, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-16778.

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In this thesis we examine the colour forecasting process, its methodology and how it is communicated and used in fashion companies. The study is foremost based on qualitative research and on semi-structured interviews with people within the forecasting industry. We have divided the data collection process that constitutes the basis of the actual forecast into steps, which consist of gathering both objective facts and more soft, subjective experiences. After having collected the data, colour forecasters start their analysis by breaking them down into thematical categories that depict specific patterns (themes). We have identified colour expertise, intuition, creativity and inspiration as the factors that help the forecaster interpret those patterns. The final forecasted colour stories are being presented in different media and contexts. Besides design style, market, customer base and lead-time, it is foremost the differentmanagement philosophies of either building creative, solid collections or fast fashion that define how to use the colour forecasting material. To help the reader understand the process we have constructed a model (aDaMas).
Program: Master in Fashion Management with specialisation in Fashion Marketing and Retailing
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PEDRONI, MARCO LUCA. "Coolhunting: la circolarità della distinzione." Doctoral thesis, Università Cattolica del Sacro Cuore, 2009. http://hdl.handle.net/10280/418.

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Obiettivo di questa tesi è una lettura del coolhunting, attività professionale ancora relativamente poco diffusa, come luogo emblematico di meccanismi simbolici cruciali per spiegare non solo il sistema della moda ma anche molti degli andamenti della produzione e del consumo di beni materiali ricchi di contenuti immateriali. Non a caso, il debito teorico di questo lavoro non riguarda solo i fashion studies a partire dal classico saggio di Simmel, ma soprattutto un autore come Pierre Bourdieu, che poche pagine ha dedicato alla moda ma ha coniato concetti, come quelli di campo, capitale culturale e simbolico, habitus e distinzione, che sono diventati imprescindibili in ogni studio di tipo culturale. La base empirica della ricerca è costituita da 42 interviste del tipo racconti di vita, che hanno coinvolto una variegata popolazione di coolhunters inseriti in agenzie o nelle imprese della moda, ricercatori e consulenti free-lance, le cui esperienze lavorative sono analiticamente descritte nei capitoli centrali della tesi. La ricostruzione del mondo del coolhunting si avvale anche di una accurata ricerca effettuata su siti web dedicati. Nel capitolo finale la prospettiva teorica e il corpus di informazioni raccolte trovano una sintesi in (a) una definizione articolata ma precisa di cool-hunter; (b) una tipologia idealtipica; (c) nel concetto bourdieusiano di distinzione, che sembra essere la posta in gioco intorno alla quale ruota tutto il mondo del coolhunting. I coolhunters emergono come intermediari culturali riconosciuti per la loro capacità di cogliere gli stili di consumo emergenti e le macrotendenze culturali per offrirli come spunto alla creatività dei produttori di oggetti di moda mainstream.
The aim of this thesis is a reading of coolhunting, an emergent professional activity, as an emblematic place of symbolic mechanisms that are crucial in order to explain not only the fashion system but also many cultural processes of the production and the consumption of material goods rich of immaterial contents. The theoretical debt does not regard only the fashion studies, beginning from the classic work of Simmel, but above all an author like Pierre Bourdieu, that has dedicated few pages to the fashion, but has coined concepts - as those of field, cultural and symbolic capital, habitus, distinction - that are nowadays essential in every cultural study. The empiric base of the research is a set of 42 in-depht interviews that have involved a heterogeneous population of coolhunters working in trend agencies or fashion companies, researchers and free-lance consultants, whose working experiences are analytically described in the central chapters of the thesis. The reconstruction of the world of the coolhunting is carried out also with a search based on dedicated websites. In the final chapter the theoretical perspective and the empirical evidences are summarized in (a) an articulate definition of coolhunter; b) an idealtypical classification of coolhunting workers; (c) in Pierre Bourdiue’s concept of distinction, that seems to be the stake that moves the field of coolhunting. The coolhunters emerge as cultural intermediaries recognized for their ability to identify the emergent styles of consumption and macro-cultural trends in order to offer them as useful ideas to the creativity of the producers of fashionable mainstream objects.
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Silva, Ana Sofia Laranjeira da. "As tendências e sua aplicação no design de moda: uma metodologia para o desenvolvimento de coleções." Master's thesis, 2016. http://hdl.handle.net/1822/56101.

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Dissertação de mestrado em Design e Marketing
A moda desempenha um papel fundamental nos dias de hoje, fruto das constantes mudanças da sociedade e do mercado necessita de uma evolução pelo estudo de novas formas, cores, fibras e texturas, de acordo com as necessidades dos consumidores. Surge então a questão: quais são as tendências da moda? Como estudá-las e as aplicar no desenvolvimento de novas coleções? Para um estudo assertivo foi realizado um estudo em campo com observação diária e anotação de dados e posteriormente a recolha de informação via questionários de opinião, numa escola e numa empresa. Procurou-se perceber qual o valor dado às tendências pelos designers e como estes as integram no seu processo criativo. Da pesquisa efetuada compreende-se que a análise das tendências da moda não é linear nem realizada de forma esquemática e pragmática, requerindo senso de estética e liberdade de pensamento. Com base nos dados recolhidos e analisando e comparando metodologias procura-se desenvolver uma abordagem ao processo criativo que permita agregar valor e ideias no desenvolvimento de coleções. Deste trabalho resulta a proposta de uma metodologia de trabalho designada “metodologia triangular”, que se aplicou num caso prático. Uma primeira análise aos resultados da aplicação desta metodologia, permitiu concluir que a adoção de médodos estruturados no pensamento criativo em design de moda permite efetuar uma pesquisa visual mais eficaz e articulada visando a aplicação de tendências no desenvolvimento de novas coleções de forma mais fluída e com resultados potencialmente melhores.
Fashion plays a key role today, the result of constant changes in society and the market requires an evolution in the study of new forms, colors, textures and fibers, according to the needs of consumers. The question then arises: what are the fashion trends? How to study them and apply them in the development of new collections? For an assertive study we conducted a field study with daily observation and data annotation and then the collection of information through opinion questionnaires, a school and a company. He tried to understand what the value given to trends by designers and how they integrate them in their creative process. From research it is understood that the analysis of fashion trends is not linear nor performed schematic and pragmatic way, which requires sense of aesthetics and freedom of thought. Based on the collected data and analyzing and comparing methodologies seeks to develop an approach to the creative process that allows adding value and ideas in the development of collections. This work results in the proposal of a work methodology called "triangular methodology", which was applied in a practical case. A first analysis of the results of the application of this methodology allowed us to conclude that the adoption of structured methodologies in creative thinking in fashion design allows a more effective and articulated visual research aiming at the application of trends in the development of new collections results better and more fluid.
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Books on the topic "Fashion trend forecasting"

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Barker, Katherine L. A study of colour and trend forecasting for the fashion industry. Manchester: UMIST, 1998.

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Fashion Trend Forecasting. King Publishing, Laurence, 2017.

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Fashion Buying: From Trend Forecasting to Shop Floor. Bloomsbury Visual Arts, 2017.

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The fashion forecasters: A hidden history of color and trend prediction. 2018.

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Payne, Alice, Ann Marie Fiore, Hyejeong Kim, and Eundeok Kim. Fashion Trends: Analysis and Forecasting. Bloomsbury Publishing Plc, 2021.

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Fashion Trends: Analysis and Forecasting. Berg Publishers, 2011.

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Payne, Alice, Ann Marie Fiore, Hyejeong Kim, and Eundeok Kim. Fashion Trends: Analysis and Forecasting. Bloomsbury Publishing Plc, 2021.

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Fashion Trends Analysis And Forecasting. Berg Publishers, 2011.

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Choklat, Aki. Menswear Trends. Bloomsbury Publishing USA, 2018.

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Book chapters on the topic "Fashion trend forecasting"

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Luce, Leanne. "Data Mining and Trend Forecasting." In Artificial Intelligence for Fashion, 141–51. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3931-5_9.

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Yu, Yong, Sau-Fun Ng, Chi-Leung Hui, Na Liu, and Tsan-Ming Choi. "Intelligent Fashion Colour Trend Forecasting Schemes: A Comparative Study." In Intelligent Fashion Forecasting Systems: Models and Applications, 147–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39869-8_8.

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Jiang, Lisheng, Huchang Liao, and Zhi Li. "Probabilistic Linguistic Linear Least Absolute Regression for Fashion Trend Forecasting." In Artificial Intelligence on Fashion and Textiles, 337–46. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99695-0_41.

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Ntalaperas, Dimitris, Iosif Angelidis, Giorgos Vafeiadis, and Danai Vergeti. "A Decision-Support System for the Digitization of Circular Supply Chains." In New Business Models for the Reuse of Secondary Resources from WEEEs, 97–107. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74886-9_8.

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AbstractAs it has been already explained, it is very important for circular economies to minimize the wasted resources, as well as maximize the utilization value of the existing ones. To that end, experts can evaluate the materials and give an accurate estimation for both aspects. In that case, one might wonder, why is a decision support system employing machine learning necessary? While a fully automated machine learning model rarely surpasses a human’s ability in such tasks, there are several advantages in employing one. For starters, human experts will be more expensive to employ, rather than use an algorithm. One could claim that research towards developing an efficient and fully automated decision support system would end up costing more than employing actual human experts. In this instance, it is paramount to think long-term. Investing in this kind of research will create systems which are reusable, extensible, and scalable. This aspect alone more than remedies the initial costs. It is also important to observe that, if the number of wastes to be processed is more than the human experts can process in a timely fashion, they will not be able to provide their services, even if employment costs were not a concern. On the contrary, a machine learning model is perfectly capable of scaling to humongous amounts of data, conducting fast data processing and decision making. For power plants with particularly fast processing needs, an automated decision support system is an important asset. Moreover, a decision support system can predict the future based on past observations. While not always entirely spot on, it can give a future estimation about aspects such as energy required, amounts of wastes produced etc. in the future. Therefore, processing plants can plan of time and adapt to specific needs. A human expert can provide this as well to some degree, but on a much smaller scale. Especially in time series forecasting, it is interesting to note that, even if a decision support model does not predict exact values, it is highly likely to predict trends of the value increasing or decreasing in certain ranges. In the next sections, we are going to describe the four machine learning models that were developed and which compose the Decision Support System of FENIX. Section 8.1 describes how we predict the quality of the extracted materials based on features such as temperature, extruder speed, etc. Section 8.2 describes the process of extracting heuristic rules based on existing results. Section 8.3 describes how FENIX provides time-series forecasting to predict the future of a variable based on past observations. Finally, Sect. 8.4 describes the process of classifying materials based on images.
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"FASHION FORECASTING AND TREND PREDICTION." In Teaching Fashion Studies. Bloomsbury Visual Arts, 2018. http://dx.doi.org/10.5040/9781350022911.pt-003.

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Bowstead, Jay McCauley, and Lili Golmohammadi. "Trend Forecasting, Taste and Fashion Production." In Teaching Fashion Studies. Bloomsbury Visual Arts, 2018. http://dx.doi.org/10.5040/9781350022911.ch-005.

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"Formats of Trend Forecasts and the Influences of Trend Forecasting on Business Decisions." In Fashion Trends. Bloomsbury Visual Arts, 2021. http://dx.doi.org/10.5040/9781350099043.ch-007.

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"The Process and Methods of Fashion Trend Analysis and Forecasting." In Fashion Trends. Bloomsbury Visual Arts, 2021. http://dx.doi.org/10.5040/9781350099043.ch-003.

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"The Role of Fashion Industry Professionals in Trend Development and Forecasting." In Fashion Trends. Bloomsbury Visual Arts, 2021. http://dx.doi.org/10.5040/9781350099043.ch-004.

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Powers, Devon. "Trending." In On Trend, 25–41. University of Illinois Press, 2019. http://dx.doi.org/10.5622/illinois/9780252042874.003.0002.

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Abstract:
Chapter 1 begins in early twentieth-century America and offers a prehistory of trend forecasting. The era saw society swiftly modernizing; in turn, the social sciences were producing a surfeit of data about life and culture. Observers, social critics, and government technocrats began to think of these data as predictive and explored how they could be used to make decisions and dampen uncertainty about the future. In light of these developments, “trends” emerged as a tool, allowing data to be used to anticipate change. The chapter highlights the 1933 study Recent Social Trends as a primary example of how trends could be used to manage uncertainty. The chapter also documents how trends served these ends in the burgeoning forecasting professions, including weather, economics, and fashion.
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Conference papers on the topic "Fashion trend forecasting"

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Ma, Yunshan, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, and Tat-Seng Chua. "Knowledge Enhanced Neural Fashion Trend Forecasting." In ICMR '20: International Conference on Multimedia Retrieval. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3372278.3390677.

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Zhao, Li, Muzhen Li, and Peng Sun. "Neo-Fashion: A Data-Driven Fashion Trend Forecasting System using Machine Learning through Catwalk Analysis." In Pivoting for the Pandemic. Iowa State University Digital Press, 2020. http://dx.doi.org/10.31274/itaa.12062.

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Reports on the topic "Fashion trend forecasting"

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Fiore, Ann Marie Marie, and Danielle S. Testa. A Fashion Trend Forecasting Course as a Gateway to Career Discovery. Ames (Iowa): Iowa State University. Library, January 2019. http://dx.doi.org/10.31274/itaa.8470.

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DuBreuil, Mikayla, and Sheng Lu. Traditional Versus Big-Data Based Fashion Trend Forecasting: An Examination Using WGSN and EDITED. Ames (Iowa): Iowa State University. Library, January 2019. http://dx.doi.org/10.31274/itaa.8246.

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